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Titre : Ionospheric multi-spacecraft analysis tools : approaches for deriving ionospheric parameters Type de document : Monographie Auteurs : Malcolm Wray Dunlop, Éditeur scientifique ; Hermann Lühr, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2020 Collection : ISSI Scientific Report Series num. 17 Importance : 288 p. ISBN/ISSN/EAN : 978-3-030-26732-2 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie
[Termes IGN] analyse harmonique
[Termes IGN] champ géomagnétique
[Termes IGN] ionosphère
[Termes IGN] méthode des moindres carrés
[Termes IGN] mission spatialeRésumé : (Auteur) This open access book provides a comprehensive toolbox of analysis techniques for ionospheric multi-satellite missions. The immediate need for this volume was motivated by the ongoing ESA Swarm satellite mission, but the tools that are described are general and can be used for any future ionospheric multi-satellite mission with comparable instrumentation. In addition to researching the immediate plasma environment and its coupling to other regions, such a mission aims to study the Earth’s main magnetic field and its anomalies caused by core, mantle, or crustal sources. The parameters for carrying out this kind of work are examined in these chapters. Besides currents, electric fields, and plasma convection, these parameters include ionospheric conductance, Joule heating, neutral gas densities, and neutral winds. Note de contenu :
1. Introduction
Malcolm Wray Dunlop and Hermann Lühr
2. Introduction to Spherical Elementary Current Systems
Heikki Vanhamäki and Liisa Juusola
3. Spherical Elementary Current Systems Applied to Swarm Data
Heikki Vanhamäki, Liisa Juusola, Kirsti Kauristie, Abiyot Workayehu and Sebastian Käki
4. Local Least Squares Analysis of Auroral Currents
Joachim Vogt, Adrian Blagau, Costel Bunescu and Maosheng He
5. Multi-spacecraft Current Estimates at Swarm
Malcolm Wray Dunlop, J.-Y. Yang, Y.-Y. Yang, Hermann Lühr and J.-B. Cao
6. Applying the Dual-Spacecraft Approach to the Swarm Constellation for Deriving Radial Current Density
Hermann Lühr, Patricia Ritter, Guram Kervalishvili and Jan Rauberg
7. Science Data Products for AMPERE
Colin L. Waters, B. J. Anderson, D. L. Green, H. Korth, R. J. Barnes and Heikki Vanhamäki
8. ESA Field-Aligned Currents—Methodology Inter-comparison Exercise
Lorenzo Trenchi and The FAC-MICE Team
9. Spherical Cap Harmonic Analysis Techniques for Mapping High-Latitude Ionospheric Plasma Flow—Application to the Swarm Satellite Mission
Robyn A. D. Fiori
10. Recent Progress on Inverse and Data Assimilation Procedure for High-Latitude Ionospheric Electrodynamics
Tomoko Matsuo
11. Estimating Currents and Electric Fields at Low Latitudes from Satellite Magnetic Measurements
Patrick Alken
12. Models of the Main Geomagnetic Field Based on Multi-satellite Magnetic Data and Gradients—Techniques and Latest Results from the Swarm Mission
Christopher C. Finlay
Correction to: Introduction to Spherical Elementary Current Systems
Heikki Vanhamäki and Liisa JuusolaNuméro de notice : 26512 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Recueil / ouvrage collectif DOI : 10.1007/978-3-030-26732-2 En ligne : http://doi.org/10.1007/978-3-030-26732-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97262
Titre : Knowledge graphs and big data processing Type de document : Monographie Auteurs : Valentina Janev, Éditeur scientifique ; Damien Graux, Éditeur scientifique ; Hajira Jabeen, Éditeur scientifique ; Emanuel Sallinger, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2020 Importance : 307 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-3-030-53199-7 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] données massives
[Termes IGN] écosystème
[Termes IGN] énergie
[Termes IGN] exploration de données
[Termes IGN] ingénierie des connaissances
[Termes IGN] intelligence artificielle
[Termes IGN] réseau sémantique
[Termes IGN] segmentation sémantique
[Termes IGN] système à base de connaissancesRésumé : (éditeur) This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required. Note de contenu : 1- Ecosystem of big data
2- Knowledge graphs: The layered perspective
3- Big data outlook, tools, and architectures
4- Creation of knowledge graphs
5- Federated query processing
6- Reasoning in knowledge graphs: An embeddings spotlight
7- Scalable knowledge graph processing using SANSA
8- Context-based entity matching for big data
9- Survey on big data applications
10- Case study from the energy domain
11-Numéro de notice : 25928 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/SOCIETE NUMERIQUE Nature : Monographie DOI : 10.1007/978-3-030-53199-7 En ligne : https://doi.org/10.1007/978-3-030-53199-7 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96189
Titre : Planar maps, random walks and circle packing : École d'été de probabilités de Saint-Flour XLVIII - 2018 Type de document : Guide/Manuel Auteurs : Asaf Nachmias, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2020 Collection : Lecture notes in Mathematics num. 2243 Importance : 120 p. ISBN/ISSN/EAN : 978-3-030-27968-4 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] arbre aléatoire
[Termes IGN] fonction harmonique
[Termes IGN] graphe planaire
[Termes IGN] modèle de MarkovIndex. décimale : 23.60 Statistiques et probabilités Résumé : (Editeur) This open access book focuses on the interplay between random walks on planar maps and Koebe’s circle packing theorem. Further topics covered include electric networks, the He–Schramm theorem on infinite circle packings, uniform spanning trees of planar maps, local limits of finite planar maps and the almost sure recurrence of simple random walks on these limits. One of its main goals is to present a self-contained proof that the uniform infinite planar triangulation (UIPT) is almost surely recurrent. Full proofs of all statements are provided. A planar map is a graph that can be drawn in the plane without crossing edges, together with a specification of the cyclic ordering of the edges incident to each vertex. One widely applicable method of drawing planar graphs is given by Koebe’s circle packing theorem (1936). Various geometric properties of these drawings, such as existence of accumulation points and bounds on the radii, encode important probabilistic information, such as the recurrence/transience of simple random walks and connectivity of the uniform spanning forest. This deep connection is especially fruitful to the study of random planar maps. The book is aimed at researchers and graduate students in mathematics and is suitable for a single-semester course; only a basic knowledge of graduate level probability theory is assumed. Note de contenu : 1. Introduction
1.1 The Circle Packing Theorem
1.2 Probabilistic Applications
2. Random Walks and Electric Networks
2.1 Harmonic Functions and Voltages
2.2 Flows and Currents
2.3 The Effective Resistance of a Network
2.4 Energy
2.5 Infinite Graphs
2.6 Random Paths
2.7 Exercises
3. The CirclePacking Theorem
3.1 Planar Graphs, Maps and Embeddings
3.2 Proof of the Circle Packing Theorem
4. Parabolic and Hyperbolic Packings
4.1 Infinite Planar Maps
4.2 The Ring Lemma and Infinite Circle Packings
4.3 Statement of the He–Schramm Theorem
4.4 Proof of the He–Schramm Theorem
4.5 Exercises
5. Planar Local Graph Limits
5.1 Local Convergenceof Graphs and Maps
5.2 The Magic Lemma
5.3 Recurrence of Bounded Degree Planar Graph Limits
5.4 Exercises
6. Recurrence of Random Planar Maps
6.1 Star-Tree Transform
6.2 Stationary Random Graphs and Markings
6.3 Proof of Theorem
7. Uniform Spanning Trees of Planar Graphs
7.1 Introduction
7.2 Basic Properties of the UST
7.3 Limits over Exhaustions:The Free and Wired USF
7.4 Planar Duality
7.5 Connectivity of the Free Forest
7.6 Exercises
8. Related TopicsNuméro de notice : 26541 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Manuel de cours DOI : 10.1007/978-3-030-27968-4 En ligne : http://doi.org/10.1007/978-3-030-27968-4 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97764 Potential of crowdsourced traces for detecting updates in authoritative geographic data / Stefan Ivanovic (2020)
Titre : Potential of crowdsourced traces for detecting updates in authoritative geographic data Type de document : Article/Communication Auteurs : Stefan Ivanovic (1988 - 2020) , Auteur ; Ana-Maria Olteanu-Raimond , Auteur ; Sébastien Mustière , Auteur ; Thomas Devogele , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2020 Collection : Lecture notes in Geoinformation and Cartography, ISSN 1863-2246 Projets : 2-Pas d'info accessible - article non ouvert / Conférence : AGILE 2019, 22nd conference on Geo-information science 17/06/2019 20/06/2019 Limassol Chypre Proceedings Springer Importance : pp 205 - 221 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] aide à la décision
[Termes IGN] appariement de données localisées
[Termes IGN] BD Topo
[Termes IGN] chemin rural
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données localisées de référence
[Termes IGN] mise à jour de base de données
[Termes IGN] montagne
[Termes IGN] route
[Termes IGN] trace GPSRésumé : (auteur) Crowdsourced traces collected by GPS devices during sports activities are now widely available on different websites. The goal of this paper is to study the potential of crowdsourced traces coming from GPS devices to highlight updates in authoritative geographic data. To reach this goal, an approach based on two steps is proposed. First, a data matching method is applied to match authoritative data and crowdsourced traces. Second, for the non-matched crowdsourced segments composing a trace, different criteria are defined to decide if whether or not, non-matched segments should be considered as an alert for update in authoritative data. The proposed approach is tested on crowdsourced traces and on BDTOPO® authoritative road and path network in mountain area. The results are promising: 727, 1 km of missing paths were found in the test area, which corresponds to 7.7% of the total length of used traces. The discovered missing paths also represent a contribution of 2.4% of the total length of BDTopo® road and path network in the test area. Numéro de notice : C2019-008 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-030-14745-7_12 Date de publication en ligne : 16/04/2019 En ligne : http://dx.doi.org/10.1007/978-3-030-14745-7_12 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92911
Titre : Representation learning for natural language processing Type de document : Monographie Auteurs : Zhiyuan Liu, Éditeur scientifique ; Yankai Lin, Éditeur scientifique ; Maosong Sun, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2020 Importance : 334 p. ISBN/ISSN/EAN : 978-981-1555732-- Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] apprentissage profond
[Termes IGN] données massives
[Termes IGN] exploration de données
[Termes IGN] représentation des connaissances
[Termes IGN] réseau neuronal convolutif
[Termes IGN] réseau sémantique
[Termes IGN] traitement du langage naturelRésumé : (Editeur) This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing. Note de contenu :
1. Representation Learning and NLP
1.1 Motivation
1.2 Why Representation Learning Is Important for NLP
1.3 Basic Ideas of Representation Learning
1.4 Development of Representation Learning for NLP
1.5 Learning Approaches to Representation Learning for NLP
1.6 Applications of Representation Learning for NLP
1.7 The Organization of This Book
2. Word Representation
2.1 Introduction
2.2 One-Hot Word Representation
2.3 Distributed Word Representation
2.4 Contextualized Word Representation
2.5 Extensions
2.6 Evaluation
3. Compositional Semantics
3.1 Introduction
3.2 Semantic Space
3.3 Binary Composition
3.4 N-Ary Composition
4. Sentence Representation
4.1 Introduction
4.2 One-Hot Sentence Representation
4.3 Probabilistic Language Model
4.4 Neural Language Model
4.5 Applications
5. Document Representation
5.1 Introduction
5.2 One-Hot Document Representation
5.3 Topic Model
5.4 Distributed Document Representation
5.5 Applications
6. Sememe Knowledge Representation
6.1 Introduction
6.2 Sememe Knowledge Representation
6.3 Applications
7. World Knowledge Representation
7.1 Introduction
7.2 Knowledge Graph Representation
7.3 Multisource Knowledge Graph Representation
7.4 Applications
8. Network Representation
8.1 Introduction
8.2 Network Representation
8.3 Graph Neural Networks
9. Cross-Modal Representation
9.1 Introduction
9.2 Cross-Modal Representation
9.3 Image Captioning
9.4 Visual Relationship Detection
9.5 Visual Question Answering
10. Resources
10.1 Open-Source Frameworks for Deep Learning
10.2 Open Resources for Word Representation
10.3 Open Resources for Knowledge Graph Representation
10.4 Open Resources for Network Representation
10.5 Open Resources for Relation Extraction
11. OutlookNuméro de notice : 26515 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.1007/978-981-15-5573-2 En ligne : http://doi.org/10.1007/978-981-15-5573-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97296 Towards interoperable research infrastructures for environmental and earth sciences / Zhiming Zhao (2020)PermalinkPermalinkPermalinkPermalinkPermalinkRecent activities of the GGOS standing committee on Performance simulations and Architectural Trade-Offs (PLATO) / Benjamin Männel (2018)PermalinkPermalinkPermalinkPermalinkAssessing the positional planimetric accuracy of DBpedia georeferenced resources / Abdelfettah Feliachi (2017)Permalink