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Eric Armengaud

Researcher at AVL

Publications -  113
Citations -  1362

Eric Armengaud is an academic researcher from AVL. The author has contributed to research in topics: Automotive industry & FlexRay. The author has an hindex of 18, co-authored 113 publications receiving 1091 citations. Previous affiliations of Eric Armengaud include Commissariat à l'énergie atomique et aux énergies alternatives & Vienna University of Technology.

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Journal ArticleDOI

Hints, neutrino bounds, and WDM constraints from SDSS DR14 Lyman-α and Planck full-survey data

TL;DR: In this article, the spectral index of the Lyman-α forest 1D flux power spectrum is used to estimate the neutrino mass under weak lensing constraints on (Ωm,σ8) and has the same small tension with Planck.
Proceedings ArticleDOI

SAHARA: a security-aware hazard and risk analysis method

TL;DR: An approach to classify the probability of security threats is presented, which can be used to determine the appropriate number of countermeasures that need to be considered and how the safety-critical contributions of successful security attacks can be quantified and processed.
Journal ArticleDOI

The one-dimensional power spectrum from the SDSS DR14 Ly$\alpha$ forests

TL;DR: In this paper, a measurement of the 1D Ly$\alpha$ forest flux power spectrum using the complete Baryon Oscillation Spectroscopic Survey (BOSS) and first extended-BOSS quasars at the Sloan Digital Sky Survey (SDSS) was presented.
Book ChapterDOI

A Review of Threat Analysis and Risk Assessment Methods in the Automotive Context

TL;DR: The recently released SAE J3061 guidebook for cyber-physical vehicle systems provides information and high-level principles for automotive organizations to identify and assess cyber-security threats and design cyber- security aware systems.
Journal ArticleDOI

Towards a Systematic Test for Embedded Automotive Communication Systems

TL;DR: This paper focuses on the test of distributed systems based on FlexRay, the protocol that is envisioned as the communication backbone for future automotive systems, and presents a decomposition of the system into layers and mechanisms, and a versatile strategy for monitoring and stimulation under various conditions.