Simulations of coronagraphy with a dynamic hologram for the direct detection of exo-planets

In a previous paper, we discussed an original solution to improve the performances of coronagraphs by adding, in the optical scheme, an adaptive hologram removing most of the residual speckle starlight. In our simulations, the detection limit in the flux ratio between a host star and a very near planet (5 lambda/D) improves over a factor 1000 (resp. 10000) when equipped with a hologram for cases of wavefront bumpiness imperfections of lambda/20 (resp. lambda/100). We derive, in this paper, the transmission accuracy required on the hologram pixels to achieve such goals. We show that preliminary tests could be performed on the basis of existing technologies.Comment: 5 pages, 6 figure

Extreme coronagraphy with an adaptive hologram

We present a solution to improve the performances of coronagraphs in general for the detection of exo-planets. We simulate several kinds of coronagraphic systems using an IDL software, with the aim of evaluating the gain obtained using an adaptive hologram. The detection limit in flux ratio between a star and a planet observed with an apodized Lyot coronagraph characterized by wavefront bumpiness imperfections of lambda/20 (resp. lambda /100) turns out to be increased by a factor 1`000 (resp. 1`000`000) when equipped with an hologram. This technique could provide a direct imaging of an exo-earth at a distance of 11 parsec with a space telescope with a mirror quality analog to the HST, and with a diameter analog to the JWST

Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images

Breast cancer is one of the most common types of cancer and leading cancer-related death causes for women. In the context of ICIAR 2018 Grand Challenge on Breast Cancer Histology Images, we compare one handcrafted feature extractor and five transfer learning feature extractors based on deep learning. We find out that the deep learning networks pretrained on ImageNet have better performance than the popular handcrafted features used for breast cancer histology images. The best feature extractor achieves an average accuracy of 79.30%. To improve the classification performance, a random forest dissimilarity based integration method is used to combine different feature groups together. When the five deep learning feature groups are combined, the average accuracy is improved to 82.90% (best accuracy 85.00%). When handcrafted features are combined with the five deep learning feature groups, the average accuracy is improved to 87.10% (best accuracy 93.00%)

A Component-based Framework for Space Domain Software Applications

International audienceThis paper presents research carried on by Thales on component based software engineering for the space domain. We outline the space domain context and give the general architecture of MyCCM, our component framework. We explain how we implemented a space-specific component framework with MyCCM and what results we got from experiments. Applying component design to on-board space applications induces a very light overhead while allowing automatic code generation, as well as code reuse and application redeployment. It thus helps cut development costs and improve the reliability of software development

Quantifying the effects of heating temperature, and combined effects of heating medium pH and recovery medium pH on the heat resistance of Salmonella typhimurium

International audienceThe influence of heating treatment temperature, pH of heating and recovery medium on the survival kinetics of Salmonella typhimurium ATCC 13311 is studied and quantified. From each non-log linear survival curve, Weibull model parameters were estimated. An average shape parameter value of 1.67 was found, which is characteristic of downward concavity curves and is in agreement with values estimated from other S. typhimurium strains. Bigelow type models quantifying the heating temperature, heating and recovery medium pH influences are fitted on scale parameter δ data (time of first decimal reduction), which reflects the bacterial heat resistance. The estimate of zT (4.64 °C) is in the range of values given in the literature for this species. The influence of pH of the heating medium on the scale parameter (zpH: 8.25) is lower than that of the recovery pH medium influence (z′pH: 3.65)

Contribution à l'étude des propriétés d'un composite PP/lin mis en oeuvre par extrusion

International audienceLe comportement mécanique d'un composite polypropylène (PP) renforcé avec des fibres de lin extrudé sous forme de bande plate a été étudié et comparé à celui du PP/talc. Ces mêmes matériaux ont aussi été injectés et leur propriétés comparées à celles des pièces extrudées. Les propriétés mécaniques et leur microstructure ont été étudiées après transformation. L'utilisation des fibres de lin comme renfort permet de dépasser les propriétés mécaniques du PP/talc tout en permettant une diminution du retrait et de la masse volumique. L'ajout d'anhydride maléique a permis une nette amélioration des performances grâce à l'amélioration de l'interface fibres/matrice. Les matériaux injectés présentent de meilleures caractéristiques mécaniques que ceux extrudés grâce à une meilleure orientation des fibres et une plus faible porosité