On adaptive wavelet estimation of a class of weighted densities

We investigate the estimation of a weighted density taking the form $g=w(F)f$, where $f$ denotes an unknown density, $F$ the associated distribution function and $w$ is a known (non-negative) weight. Such a class encompasses many examples, including those arising in order statistics or when $g$ is related to the maximum or the minimum of $N$ (random or fixed) independent and identically distributed (\iid) random variables. We here construct a new adaptive non-parametric estimator for $g$ based on a plug-in approach and the wavelets methodology. For a wide class of models, we prove that it attains fast rates of convergence under the $\mathbb{L}_p$ risk with $p\ge 1$ (not only for $p = 2$ corresponding to the mean integrated squared error) over Besov balls. The theoretical findings are illustrated through several simulations

Numerical simulation of solar cells besed CZTS buffer layer (ZnO1-XSX) using SCAPS-1D software

Cds buffer layer has many advantages such as large bandgap, and the carrier density. Otherwise, the presence of cadmium is an inconvenient. Research work, are shifted on the possibility of replacing CdS by a buffer layer devoid of cadmium. This manuscript presents the numerical study, using SCAPS-1D program, the effects of sulfur content in the buffer layer Zn (O,S) on the electrical parameters of the solar cell ZnO: Al / i-ZnO / Zn (O, S) / CZTS /. Changes in the band gap and electron affinity of Zn (O, S) were calculated from the law of Vegard. The numerical results of the thickness of the absorbent layer CZTS equal to 2.5μm, show that from the sulfur content equals to 45% we can find the same results with CdS, an efficiency varies slightly, about 19%.Keywords: CZTS; ZnO1-xSx; CdS; SCAPS; Solar cell

Cooperative method and performance evaluation of encephalon segmentation in magnetic resonance imaging

Some complex applications in medical imaging need to combine results coming from different numerical operators referred as t o edges — and regions — operators . To improve success of segmentation, the idea proposed is to combine region and active contou r segmentations. This cooperative method takes advantage of both two approaches . In the first step, we use tools from mathematica l morphology and region growing algorithms for the region segmentation in order to get an automated initialization of the activ e contour model . In the second step, the physically based active model, considered as a set of masses linked by springs, is used i n order to refine the delineation of objects obtained by the first approach undergoing an elastic deformation . Segmentation results are illustrated on encephalon extraction on 3D MRI data sets . The parameters of the active contour model are evaluated an d discussed . Results are quantified using a phantom, by means of some global and local measure functions, and show the interes t of the active contour for a refined delineation of the brain .Certaines applications complexes en imagerie médicale combinent des résultats provenant de différents opérateurs numériques qui font référence à des méthodes type région et contour. Pour améliorer la qualité de la segmentation, l'idée proposée est de combiner la segmentation région et la segmentation contour. Cette méthode allie les avantages de ces deux approches prises séparément, pans un premier temps, on utilise des outils de morphologie mathématique et des algorithmes de croissance de régions en vue d'obtenir une initialisation automatique approximative pour l'approche contour. Dans un deuxième temps, le modèle physique du contour actif (contour déformable), qui assimile le contour à un certain nombre de masses ponctuelles reliées par des ressorts, permet d'affiner le résultat de l'approche région sous l'action d'une déformation élastique. Les résultats sont présentés pour l'extraction de l'encéphale sur des données IRM 3D. Les paramètres du modèle de contour actif sont évalués et discutés. Les résultats sont quantifiés par des fonctions de mesures globales et locales à travers un fantôme réaliste, et montrent l'amélioration apportée par le contour actif

Source detection using a 3D sparse representation: application to the Fermi gamma-ray space telescope

The multiscale variance stabilization Transform (MSVST) has recently been proposed for Poisson data denoising. This procedure, which is nonparametric, is based on thresholding wavelet coefficients. We present in this paper an extension of the MSVST to 3D data (in fact 2D-1D data) when the third dimension is not a spatial dimension, but the wavelength, the energy, or the time. We show that the MSVST can be used for detecting and characterizing astrophysical sources of high-energy gamma rays, using realistic simulated observations with the Large Area Telescope (LAT). The LAT was launched in June 2008 on the Fermi Gamma-ray Space Telescope mission. The MSVST algorithm is very fast relative to traditional likelihood model fitting, and permits efficient detection across the time dimension and immediate estimation of spectral properties. Astrophysical sources of gamma rays, especially active galaxies, are typically quite variable, and our current work may lead to a reliable method to quickly characterize the flaring properties of newly-detected sources.Comment: Accepted. Full paper will figures available at http://jstarck.free.fr/aa08_msvst.pd

Approche markovienne pour la segmentation 3D des tissus cérébraux en IRM

La segmentation des matières grise, blanche et liquide céphalo-rachidien (LCR) en IRM est rendue difficile due à l'effet de volume partiel. Pour s'affranchir de ce problème, nous proposons un modèle de classes mixtes. Le nombre de classes dans un volume d'encéphale est choisi égal à cinq, ce qui est confirmé par l'analyse de l'histogramme. En utilisant une modélisation par champs aléatoires de Markov, notre méthode estime les pourcentages de trois tissus purs dans chaque voxel en deux étapes. Dans un premier temps, les cinq classes ( trois classes purs et deux classes supplémentaires correspondant aux mélanges matières grise-matière blanche et matière grise-LCR) sont segmentées. Les volumes partiels sont ensuite estimés sur les deux classes mixtes. La méthode a été testée sur plusieurs volumes cérébraux en IRM anatomique

FASTLens (FAst STatistics for weak Lensing) : Fast method for Weak Lensing Statistics and map making

With increasingly large data sets, weak lensing measurements are able to measure cosmological parameters with ever greater precision. However this increased accuracy also places greater demands on the statistical tools used to extract the available information. To date, the majority of lensing analyses use the two point-statistics of the cosmic shear field. These can either be studied directly using the two-point correlation function, or in Fourier space, using the power spectrum. But analyzing weak lensing data inevitably involves the masking out of regions or example to remove bright stars from the field. Masking out the stars is common practice but the gaps in the data need proper handling. In this paper, we show how an inpainting technique allows us to properly fill in these gaps with only $N \log N$ operations, leading to a new image from which we can compute straight forwardly and with a very good accuracy both the pow er spectrum and the bispectrum. We propose then a new method to compute the bispectrum with a polar FFT algorithm, which has the main advantage of avoiding any interpolation in the Fourier domain. Finally we propose a new method for dark matter mass map reconstruction from shear observations which integrates this new inpainting concept. A range of examples based on 3D N-body simulations illustrates the results.Comment: Final version accepted by MNRAS. The FASTLens software is available from the following link : http://irfu.cea.fr/Ast/fastlens.software.ph

Extraction et partitionnement de l'encéphale par un modèle de contours actifs

La segmentation des structures anatomiques à partir d'IRM fait maintenant l'objet d'un intérêt certain. Pour améliorer la qualité de la segmentation, l'idée proposée est de combiner la segmentation région et la segmentation contour. La segmentation région permet d'avoir une initialisation automatique approximative pour l'approche contours. Cette dernière assimile le contour à un certain nombre de masses ponctuelles reliées par des ressorts , converge vers un état d'équilibre sous l'action d 'une déformation élastique. Les résultats sont présentés pour l'extraction et le partitionnement de l'encéphale sur des données IRM 3D chez l'être humain et le primate. Ces résultats sont ensuite validés par des mesures comme le taux de recouvrement et la carte de distance

PENGARUH PELATIHAN KERJA DAN PENGEMBANGAN SDM TERHADAP KINERJA KARYAWAN

ABSTRAK Penelitian ini bertujuan untuk menganalisis pengaruh pelatihan kerja dan pengembangan sumber daya manusia terhadap kinerja karyawan, Survei pada karyawan di PT. Bridgestone Tire Indonesia. Metode penelitian deskriptif digunakan untuk menjelaskan pelaksanaan pelatihan, proses pengembangan SDM serta kondisi kinerja karyawan selama ini. Metode verifikatif path analsys digunakan untuk menjelaskan hubungan korelasional baik langsung maupun tidak langsung dari variable endogen dan eksogen yang diteliti. Sampel dikumpulkan menggunakan metode Proportionate Stratified Random Sampling dengan total sampel 153 dari populasi 250 karyawan. Hasil penelitian menjukkan bahwa tedapat hubungan korelasional antara varabel pelatihan dan pengebangan SDM yang memungkinkan terjadinya hubunganj jalur dari ketiga variable yang diteliti. Pengaruh langsung dan tidak langsung Pengembangan SDM lebih tinggi dibandingkan dengan pelangaruh pelatihan terhadap kinerja karyawan di perusahaan tersebut. Kata kunci: Pelatihan Kerja, Pengembangan Sumber Daya Manusia, Kinerja Karyawan

A review of fMRI simulation studies

Simulation studies that validate statistical techniques for fMRI data are challenging due to the complexity of the data. Therefore, it is not surprising that no common data generating process is available (i.e. several models can be found to model BOLD activation and noise). Based on a literature search, a database of simulation studies was compiled. The information in this database was analysed and critically evaluated focusing on the parameters in the simulation design, the adopted model to generate fMRI data, and on how the simulation studies are reported. Our literature analysis demonstrates that many fMRI simulation studies do not report a thorough experimental design and almost consistently ignore crucial knowledge on how fMRI data are acquired. Advice is provided on how the quality of fMRI simulation studies can be improved