In this report, we present a data-driven parallelization technique of sequential programs. The main originality of our approach is an absorption mechanism using a speci c wait/signal mechanism based on counters called structural clocks. This mechanism allows to perform unmatching send/receive instructions. Therefore, our parallelization technique can express not foreseeable communications invol...

This paper presents a new pixel labeling algorithm for complex histology image segmentation. For each image pixel, a Gaussian mixture model is applied to estimate its neighborhood intensity distributions. With this local distribution fitting, a set of pixels having a full set of source classes (e.g. nuclei, stroma, connective tissue, and background) in their neighborhoods are identified as the ...

-Wind energy has been used for navigation and agriculture. Recently, wind energy is given a lot of attention because of the focus on renewable energy. Wind energy growth in Asia is currently on the rise. Both India and China are leading with more installed capacity and manufacturing facilities. In Malaysia, wind energy conversion is also given a serious consideration. The potential for wind ene...

A robust estimation procedure for mixture linear regression models is proposed by assuming that the error terms follow a Laplace distribution. The estimation procedure is implemented by an EM algorithm based on the fact that the Laplace distribution is a scale mixture of a normal distribution. Finite sample performance of the proposed algorithm is evaluated by numerical simulation studies. The ...

We propose a new robust estimator for parameter estimation in highly noisy data with multiple structures and without prior information on the noise scale of inliers. This is a diagnostic method that uses random sampling like RANSAC, but adaptively estimates the inlier scale using a novel adaptive scale estimator. The residual distribution model of inliers is assumed known, such as a Gaussian di...

We present a new multi-component spectral energy distribution (SED) decomposition method and use it to analyze the ultraviolet to millimeter wavelength SEDs of a sample of dusty infrared-luminous galaxies. SEDs are constructed from spectroscopic and photometric data obtained with the Spitzer Space Telescope in conjunction with photometry from the literature. Each SED is decomposed into emission...

This short communication uses a simple experiment to show that fitting to a power law distribution by using graphical methods based on linear fit on the log-log scale is biased and inaccurate. It shows that using maximum likelihood estimation (MLE) is far more robust. Finally, it presents a new table for performing the Kolmogorov-Smirnof test for goodness-of-fit tailored to power-law distributi...

The accurate estimation of true prevalence and concentration of microorganisms in foods is an important element of quantitative microbiological risk assessment (QMRA). This estimation is often based on microbial detection and enumeration data. Among such data are artificial zero counts, that originated by chance from contaminated food products. When these products are not differentiated from un...

This paper presents a new region-based active contour model in a variational level set formulation for image segmentation. In our model, the local image intensities are described by Gaussian distributions with different means and variances. We define a local Gaussian distribution fitting energy with a level set function and local means and variances as variables. The energy minimization is achi...

The lognormal distribution is commonly used to model certain types of data that arise in several fields of engineering as, for example, different types of lifetime data or coefficients of wear and friction. However, a generalized form of the lognormal distribution can be used to provide better fits for many types of experimental or observational data. In this paper, a Bayesian analysis of a gen...