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Pierre-Alexandre Hébert

Bio: Pierre-Alexandre Hébert is an academic researcher from University of Technology of Compiègne. The author has contributed to research in topics: Liquid-crystal display & Liquid crystal. The author has an hindex of 2, co-authored 2 publications receiving 105 citations.

Papers
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Journal ArticleDOI
TL;DR: Nonparametric rank-based statistics depending only on linear orderings of the observations are extended to fuzzy data, leading to the concepts of fuzzy p-value, and graded rejection of the null hypothesis at a given significance level.

93 citations

Journal ArticleDOI
TL;DR: Two algorithms are proposed and illustrated that represent both the structure and the vagueness of dissimilarity measurements in a low-dimensional space using the Euclidean and spherical models.

14 citations

Journal ArticleDOI
31 Dec 2022-Detritus
TL;DR: In this paper , an orderly, manual LCD dismantling line is put into operation for differentiated recycling of electronic boards, cold cathode lamps that may contain mercury, polymers, metals, and other valuable materials.
Abstract: For several decades, Liquid Crystal Displays (LCDs) have been widely used in televisions, laptops, mobile phones, and other devices. Nowadays, liquid crystals (LCs) represent an important economic value of the recycling system of LCDs. The reuse of these organic molecules could become a profitable basis since it permits to preserve the value of these materials. In this context, the general objective of this work focuses on the recovery of LCs as well as on other valuable materials present in end-of-life LCDs. An orderly, manual LCD dismantling line is put into operation for differentiated recycling of electronic boards, cold cathode lamps that may contain mercury, polymers, metals, and other valuable materials. There is also an extraction line where LCD panels are opened and exposed to an ultrasonically activated organic solvent bath to recover LCs. The resulting solution contains LCs, solvent, organic and inorganic impurities. The LCs mixtures were purified and then characterized mainly by spectroscopic, chromatographic, and thermal techniques. A study of the influence of adding diamond nanoparticles at 0.05, 0.1 and 0.2 wt% to recycled LCs was also performed using dielectric spectroscopy. Dielectric properties of LCs were measured at room temperature, using an impedance analyzer in the frequency range from 0.1 to 106 Hz.

3 citations

Journal ArticleDOI
TL;DR: In this paper , the dielectric behavior and electrical conductivity response of recycled nematic liquid crystals (LCs) were studied over a wide range of frequencies (0.1 to 106 Hz) and temperatures (100 to −20 °C).

2 citations

Proceedings ArticleDOI
01 Jan 2022
TL;DR: In this paper , a multilevel approach is considered in order to characterise general patterns up to different shapes and densities, and both a priori and a posteriori split criteria are discussed and evaluated.
Abstract: : Clustering algorithms based on split-and-merge concept, divisive or agglomerative process are widely developed to extract patterns with different shapes, sizes and densities. Here a multilevel approach is considered in order to characterise general patterns up to finer shapes. This paper focus on the contribution of both fuzzy and evidential models to build a relevant divisive clustering. Algorithms and both a priori and a posteriori split criteria are discussed and evaluated. Basic crisp/fuzzy/evidential algorithms are compared to cluster four datasets within a multilevel approach. Finally, same framework is also applied in embedded spectral space in order to give an overall comparison.

Cited by
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Journal ArticleDOI
TL;DR: An overview of numerical possibility theory is proposed, showing that some notions in statistics are naturally interpreted in the language of this theory and providing a natural definition of a subjective possibility distribution that sticks to the Bayesian framework of exchangeable bets.

411 citations

Journal ArticleDOI
TL;DR: This work proposes a variant of the EM algorithm that iteratively maximizes the maximization of a generalized likelihood criterion, which can be interpreted as a degree of agreement between the statistical model and the uncertain observations.
Abstract: We consider the problem of parameter estimation in statistical models in the case where data are uncertain and represented as belief functions. The proposed method is based on the maximization of a generalized likelihood criterion, which can be interpreted as a degree of agreement between the statistical model and the uncertain observations. We propose a variant of the EM algorithm that iteratively maximizes this criterion. As an illustration, the method is applied to uncertain data clustering using finite mixture models, in the cases of categorical and continuous attributes.

249 citations

Journal ArticleDOI
TL;DR: In spite of a growing literature concerning the development and application of fuzzy techniques in statistical analysis, the need is felt for a more systematic insight into the potentialities of cross fertilization between Statistics and Fuzzy Logic.

129 citations

Journal ArticleDOI
01 May 2013
TL;DR: The Wilcoxon signed-rank test is extended to the case where the available observations are imprecise quantities, rather than crisp, and the concept of critical value is generalized to the cases when the significance level is given by a fuzzy number.
Abstract: This paper extends the Wilcoxon signed-rank test to the case where the available observations are imprecise quantities, rather than crisp. To do this, the associated test statistic is extended, using the α-cuts approach. In addition, the concept of critical value is generalized to the case when the significance level is given by a fuzzy number. Finally, to accept or reject the null hypothesis of interest, a preference degree between two fuzzy sets is employed for comparing the observed fuzzy test statistic and fuzzy critical value.

107 citations

Journal ArticleDOI
TL;DR: It is shown that the EM algorithm may be used for estimating the parameters in a parametric statistical model when the observations are fuzzy and are assumed to be related to underlying crisp realizations of a random sample.

101 citations