Proverbes, dictons et expressions imagées dans l’enseignement/apprentissage du FLE, dans le secondaire au Cap-Vert.

Pour bien maîtriser une langue, il faut sans doute en avoir une connaissance la plus large possible, ce qui demande alors l’enseignement/apprentissage de tous les éléments qui la composent. Dans ce cas, il est très important de savoir quels sont, parmi ces éléments, ceux qui sont amenés en classe et comment ils y sont présentés. Il y en a certains qui ne fi-gurent pas dans le programme destiné à l’enseignement/apprentissage de la langue fran-çaise. S’ils l’étaient, probablement ils seraient enseignés. Mais, d’après notre constat, non seulement ils ne figurent pas, comme ils ne sont pas ou presque pas traités en cours par l’initiative des professeurs, bien qu’ils soient parmi les éléments les plus importants dans l’apprentissage d’une langue. Très souvent, ce sont ces éléments qui sont à la base de la motivation pour l’apprentissage des langues puisqu’ils constituent, d’une certaine manière, le charme et la beauté d’une langue. Nous en avons pris trois (proverbe, dicton et expres-sion imagée), qui peuvent représenter la manière de vivre ; de penser ; la culture, les cou-tumes et les habitudes d’un peuple. Il faut préciser que ce constat nous l’avons fait depuis longtemps. Par conséquent, nous avons décidé de traduire l’inquiétude que cette problématique provoque chez nous en ce travail de recherche qui a été mené sous le thème de : Proverbes, dictons et expres-sions imagées dans l’enseignement/apprentissage du FLE, dans le secondaire au Cap- Vert. Dans l’ensemble, ce travail est composé de trois parties. Dans la première partie, après les consultations de documents, nous avons proposé une réflexion sur le proverbe, le dicton et l’expression imagée en ce qui concerne leur origine et leur contexte social, temporel, leur durée, et leur situation actuelle par rapport à leur utilisation ou leur étude. Nous en avons également présenté quelques définitions, en insistant sur la distinction entre les mêmes, vu que pendant les recherches, nous avons constaté qu’il y a parfois, une confusion entre eux. Puis, dans la deuxième partie, à travers des enquêtes qui ont été menées sur le terrain dans quelques lycées de Praia, nous avons présenté sous forme d’analyse, la situation ac-tuelle concernant le recours aux proverbes, dictons et expressions imagées par le professeur dans ses cours, bien comme l’intérêt et la motivation des élèves face aux mêmes. Finalement, dans la troisième et dernière partie, nous avons dressé une liste composée de proverbes, dictons et expressions imagées que nous avons fait accompagner de leur pays d’origine, quand cela a été possible. Ils ont été analysés et nous avons essayé de montrer également, l’utilité pratique de leur message, soit pour les élèves à l’école, soit d’une ma-nière plus générale, pour toute la vie dans la société. Pour donner un caractère pratique à notre travail, nous avons fait quelques proposi-tions de techniques d’exploitation de proverbes, dictons et expressions imagées, dans les classes. C’est-à-dire, nous avons essayé d’apporter des suggestions qui peuvent être appli-quées à un éventuel engagement de la part des professeurs ou d’autres intervenants concer-nés à la résolution de la problématique qui a légitimé notre recherche.

Snapshot gradient-recalled echo-planar images of rat brains at long echo time at 9.4 T.

With improved B 0 homogeneity along with satisfactory gradient performance at high magnetic fields, snapshot gradient-recalled echo-planar imaging (GRE-EPI) would perform at long echo times (TEs) on the order of T2*, which intrinsically allows obtaining strongly T2*-weighted images with embedded substantial anatomical details in ultrashort time. The aim of this study was to investigate the feasibility and quality of long TE snapshot GRE-EPI images of rat brain at 9.4 T. When compensating for B 0 inhomogeneities, especially second-order shim terms, a 200 x 200 microm2 in-plane resolution image was reproducibly obtained at long TE (>25 ms). The resulting coronal images at 30 ms had diminished geometric distortions and, thus, embedded substantial anatomical details. Concurrently with the very consistent stability, such GRE-EPI images should permit to resolve functional data not only with high specificity but also with substantial anatomical details, therefore allowing coregistration of the acquired functional data on the same image data set.

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

A Motion compensated filtering approach to remove sunlight flicker in shallow water images

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach

A fast Bayesian reconstruction algorithm for emission tomography with entropy prior converging to feasible images

The development and tests of an iterative reconstruction algorithm for emission tomography based on Bayesian statistical concepts are described. The algorithm uses the entropy of the generated image as a prior distribution, can be accelerated by the choice of an exponent, and converges uniformly to feasible images by the choice of one adjustable parameter. A feasible image has been defined as one that is consistent with the initial data (i.e. it is an image that, if truly a source of radiation in a patient, could have generated the initial data by the Poisson process that governs radioactive disintegration). The fundamental ideas of Bayesian reconstruction are discussed, along with the use of an entropy prior with an adjustable contrast parameter, the use of likelihood with data increment parameters as conditional probability, and the development of the new fast maximum a posteriori with entropy (FMAPE) Algorithm by the successive substitution method. It is shown that in the maximum likelihood estimator (MLE) and FMAPE algorithms, the only correct choice of initial image for the iterative procedure in the absence of a priori knowledge about the image configuration is a uniform field.