Institution
University of Grenoble
Education•Saint-Martin-d'Hères, France•
About: University of Grenoble is a education organization based out in Saint-Martin-d'Hères, France. It is known for research contribution in the topics: Population & Context (language use). The organization has 25658 authors who have published 45143 publications receiving 909760 citations.
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01 Jan 2018
TL;DR: The aim of this chapter is to act as a primer for those wanting to learn about Runtime Verification, providing an overview of the main specification languages used for RV and introducing the standard terminology necessary to describe the monitoring problem.
Abstract: The aim of this chapter is to act as a primer for those wanting to learn about Runtime Verification (RV) We start by providing an overview of the main specification languages used for RV We then introduce the standard terminology necessary to describe the monitoring problem, covering the pragmatic issues of monitoring and instrumentation, and discussing extensively the monitorability problem
191 citations
TL;DR: The albedo of the Greenland ice sheet has declined in recent years as discussed by the authors, which is linked to an increase in the impurity content of snow in the Greenland permafrost.
Abstract: The albedo of the Greenland ice sheet has declined in recent years. Analyses of satellite data, combined with numerical simulations, suggest that Greenland’s darkening is tied to an increase in the impurity content of snow.
191 citations
TL;DR: A review of a total of 63 performance indicators partitioned into four groups according to their properties: cardinality, convergence, distribution and spread is proposed.
190 citations
TL;DR: This work develops an efficient reliability method which takes advantage of the Adaptive Support Vector Machine (ASVM) and the Monte Carlo Simulation (MCS), leading to accurate estimation of failure probability with rather low computational cost.
190 citations
TL;DR: DAPAR and ProStaR are software tools to perform the statistical analysis of label-free XIC-based quantitative discovery proteomics experiments and contain procedures to filter, normalize, impute missing value, aggregate peptide intensities, perform null hypothesis significance tests and select the most likely differentially abundant proteins with a corresponding false discovery rate.
Abstract: DAPAR and ProStaR are software tools to perform the statistical analysis of label-free XIC-based quantitative discovery proteomics experiments. DAPAR contains procedures to filter, normalize, impute missing value, aggregate peptide intensities, perform null hypothesis significance tests and select the most likely differentially abundant proteins with a corresponding false discovery rate. ProStaR is a graphical user interface that allows friendly access to the DAPAR functionalities through a web browser. AVAILABILITY AND IMPLEMENTATION DAPAR and ProStaR are implemented in the R language and are available on the website of the Bioconductor project (http://www.bioconductor.org/). A complete tutorial and a toy dataset are accompanying the packages. CONTACT samuel.wieczorek@cea.fr, florence.combes@cea.fr, thomas.burger@cea.fr.
190 citations
Authors
Showing all 25961 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Dieter Lutz | 139 | 671 | 67414 |
| Marcella Bona | 137 | 1391 | 92162 |
| Nicolas Berger | 137 | 1581 | 96529 |
| Cordelia Schmid | 135 | 464 | 103925 |
| J. F. Macías-Pérez | 134 | 486 | 94715 |
| Marina Cobal | 132 | 1078 | 85437 |
| Lydia Roos | 132 | 1284 | 89435 |
| Tetiana Hryn'ova | 131 | 1059 | 84260 |
| Johann Collot | 131 | 1018 | 82865 |
| Remi Lafaye | 131 | 1012 | 83281 |
| Jan Stark | 131 | 1186 | 87025 |
| Sabine Crépé-Renaudin | 129 | 1142 | 82741 |
| Isabelle Wingerter-Seez | 129 | 930 | 79689 |
| James Alexander | 129 | 886 | 75096 |
| Jessica Levêque | 129 | 1006 | 70208 |