Numérique

Résumé

On dit numérique une information qui se présente sous forme de nombres associés à une indication de la grandeur physique à laquelle ils s'appliquent, permettant les calculs, les statistiques, la vérification des modèles mathématiques. Numérique s'oppose en ce sens à « analogique » et, pour le calcul, à « algébrique ». On a pris l'habitude de désigner comme numériques les données informatiques. Elles sont traitées par les ordinateurs, développés depuis la seconde moitié du à partir de machines à calculer programmables. Par synecdoque, on appelle numérique tout ce qui fait appel à des systèmes électroniques construits sur des fonctions logiques, auxquelles se réduisent les calculs arithmétiques. La culture numérique désigne, par extension, les relations sociales dans les circonstances où dominent les médias reposant sur ces systèmes. Sens propre On dit « numérique » une information qui se présente sous forme de nombres associés à une indication de la grandeur physique à l

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https://fr.wikipedia.org/wiki/Num%C3%A9rique

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Un ordinateur est un système de traitement de l'information programmable tel que défini par Alan Turing et qui fonctionne par la lecture séquentielle d'un ensemble d'instructions, organisées en progr

vignette|Symbole normé du convertisseur analogique numérique Un convertisseur analogique-numérique (CAN, parfois convertisseur A/N, ou en anglais ADC pour Analog to Digital Converter ou plus simpleme

L'électronique numérique concerne le système ou la technologie appliquée dont les caractéristiques sont exprimées par des valeurs de nombres, en anglais digital signifiant « chiffre ». La meilleure

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Statistical physics of vaccination

Marcel Salathé, Zhen Wang

Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination one of the most important preventive measures of modern times is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research. (C) 2016 Elsevier B.V. All rights reserved.

Elsevier Science Bv2016

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Graph integration of structured, semistructured and unstructured data for data journalism

Angelos Christos Anadiotis, Jingmao You

Digital data is a gold mine for modern journalism. However, datasets which interest journalists are extremely heterogeneous, ranging from highly structured (relational databases), semi-structured (JSON, XML, HTML), graphs (e.g., RDF), and text. Journalists (and other classes of users lacking advanced IT expertise, such as most non-governmental-organizations, or small public administrations) need to be able to make sense of such heterogeneous corpora, even if they lack the ability to define and deploy custom extract-transform-load workflows, especially for dynamically varying sets of data sources. We describe a complete approach for integrating dynamic sets of heterogeneous datasets along the lines described above: the challenges we faced to make such graphs useful, allow their integration to scale, and the solutions we proposed for these problems. Our approach is implemented within the ConnectionLens system; we validate it through a set of experiments. (C) 2021 Elsevier Ltd. All rights reserved.

PERGAMON-ELSEVIER SCIENCE LTD2022

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Nowadays digital signal processing systems used for radar applications, communication systems or RF measurement equipments, require very high sample-rates. Sometimes these sample-rates are beyond the possibilities offered by conventional ADCs. To overcome these limits parallel architectures have been developed. The most commonly used it the one called "time-interleaved" conversion. This technique allows to achieve very-high sample-rates with circuits working at a lower frequency. The accuracy of "time-interleaved" systems is sensitive to sample-time errors. Some calibration techniques have been developed to reduce this sensitivity. They involve very sophisticated digital signal processing and, in most of the cases, they are not directly implemented on silicon but applied on measurement results in software. The goal of this thesis is to study the feasibility of a new parallel architecture for analog-to-digital conversion. This architecture must present a higher robustness to sample-time errors. The first part of this work is dedicated to time-interleaved converter. An analysis of their sensitivity to several imperfections, such as mismatches and systematic and random sample-time error is presented. This analysis is followed by a description of time-interleaved converter evolution, since the first implemented prototype to the current state of the art of the domain. The second part of this thesis focuses on the development of the new conversion technique called "frequency-interleaved". Two different approaches are studied: the first one is based on a Fourier series decomposition of the signal to convert and the second one is based on a Walsh series decomposition. During this study, theoretical and practical aspects are faced the one with the other, to combine signal processing and microelectronics together. It appears that the Fourier series approach offers modest performances and presents serious problems of implementation. Based on this study, the design of functional blocks of a Walsh series based system is proposed.

EPFL2009

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EPFL2009