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Institution

Mines ParisTech

EducationParis, France
About: Mines ParisTech is a education organization based out in Paris, France. It is known for research contribution in the topics: Finite element method & Microstructure. The organization has 6564 authors who have published 11676 publications receiving 359898 citations. The organization is also known as: École nationale supérieure des mines de Paris & École des mines de Paris.


Papers
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Journal ArticleDOI
TL;DR: In this article, the formation of cup-cone fracture in round bars and of slant fracture in plane strain specimens using the finite element (FE) method was studied using the Rousselier model and the Gurson model.

198 citations

Proceedings ArticleDOI
16 Dec 2009
TL;DR: A new version of the extended Kalman filter (EKF) is proposed for nonlinear systems possessing symmetries, which uses a geometrically adapted correction term based on an invariant output error to result in a better convergence of the estimation.
Abstract: A new version of the Extended Kalman Filter (EKF) is proposed for nonlinear systems possessing symmetries. Instead of using a linear correction term based on a linear output error, it uses a geometrically adapted correction term based on an invariant output error; in the same way the gain matrix is not updated from of a linear state error, but from an invariant state error. The benefit is that the gain and covariance equations converge to constant values on a much bigger set of trajectories than equilibrium points as is the case for the EKF, which should result in a better convergence of the estimation. This filter is applied to the practically relevant problem of estimating the velocity and attitude of a moving rigid body, e.g. an aircraft, from GPS velocity, inertial and magnetic measurements. In this context it can be seen as an extension of the “Multiplicative EKF” often used for quaternion estimation.

198 citations

Journal ArticleDOI
TL;DR: Dechezlepretre et al. as mentioned in this paper used the same data and similar econometric models to explain inter-country differences in transfer rates of clean development mechanism (CDM) projects.

197 citations

Journal ArticleDOI
TL;DR: A sequential denotational semantics for sequential programming languages is provided, based on a new notion of sequential algorithm on the Kahn-Plotkin concrete data structures, which form a cartesian closed category with straightforward solutions to recursive domain equations.

197 citations

Journal ArticleDOI
TL;DR: New structural statistical matrices which are gray level size zone matrix (SZM) texture descriptor variants which characterizes the DNA organization during the mitosis, according to zone intensities radial distribution are presented.
Abstract: This paper presents new structural statistical matrices which are gray level size zone matrix (SZM) texture descriptor variants. The SZM is based on the cooccurrences of size/intensity of each flat zone (connected pixels with the same gray level). The first improvement increases the information processed by merging multiple gray-level quantizations and reduces the required parameter numbers. New improved descriptors were especially designed for supervised cell texture classification. They are illustrated thanks to two different databases built from quantitative cell biology. The second alternative characterizes the DNA organization during the mitosis, according to zone intensities radial distribution. The third variant is a matrix structure generalization for the fibrous texture analysis, by changing the intensity/size pair into the length/orientation pair of each region.

196 citations


Authors

Showing all 6591 results

NameH-indexPapersCitations
Francis Bach11048454944
Olivier Delattre10349039258
Richard M. Murray9771169016
Bruno Latour9636494864
George G. Malliaras9438228533
George S. Wilson8871633034
Zhong-Ping Jiang8159724279
F. Liu8042823869
Kazu Suenaga7532926287
Carlo Adamo7544436092
Edith Heard7519623899
Enrico Zio73112723809
John J. Jonas7037921544
Bernard Asselain6940923648
Eric Guibal6929416397
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202315
202264
2021274
2020260
2019250
2018249