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Titre : Urban Informatics Type de document : Monographie Auteurs : Wenzhong Shi, Editeur scientifique ; Michael F. Goodchild, Editeur scientifique ; Michael Batty, Editeur scientifique ; et al., Auteur Editeur : Springer Nature Année de publication : 2021 Collection : The Urban Book Series Importance : 941 p. ISBN/ISSN/EAN : 978-981-1589836-- Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Urbanisme
[Termes descripteurs IGN] données massives
[Termes descripteurs IGN] infrastructure urbaine de données localisées
[Termes descripteurs IGN] mobilité urbaine
[Termes descripteurs IGN] planification urbaine
[Termes descripteurs IGN] pollution
[Termes descripteurs IGN] sécurité publique
[Termes descripteurs IGN] système d'information géographique
[Termes descripteurs IGN] ville durable
[Termes descripteurs IGN] ville intelligenteRésumé : (éditeur) This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity. Note de contenu : 1- Introduction
2- Dimensions of Urban Science
3- Urban Systems and ApplicationsNuméro de notice : 28559 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Monographie DOI : 10.1007/978-981-15-8983-6 En ligne : https://link.springer.com/book/10.1007/978-981-15-8983-6 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97592
Titre : AI based robot safe learning and control Type de document : Monographie Auteurs : Xuefeng Zhou ·, Auteur ; Shuai Li, Auteur ; et al., Auteur Editeur : Springer Nature Année de publication : 2020 Importance : 127 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-981-1555039-- Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes descripteurs IGN] contrainte d'objet
[Termes descripteurs IGN] optimisation (mathématiques)
[Termes descripteurs IGN] réseau neuronal récurrent
[Termes descripteurs IGN] robotique
[Termes descripteurs IGN] sécurité
[Termes descripteurs IGN] système de contrôle
[Termes descripteurs IGN] vitesse angulaireRésumé : (éditeur) This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors’ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities. Note de contenu : 1- Adaptive Jacobian based trajectory tracking for redundant manipulators with model uncertainties in repetitive tasks
2- RNN based trajectory control for manipulators with uncertain kinematic parameters
3- RNN based adaptive compliance control for robots with model uncertainties
4- Deep RNN based obstacle avoidance control for redundant manipulators
5- Optimization-based compliant control for manipulators under dynamic obstacle constraints
6- RNN for motion-force control of redundant manipulators with optimal joint torqueNuméro de notice : 28518 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Monographie DOI : sans En ligne : https://directory.doabooks.org/handle/20.500.12854/32049 Format de la ressource électronique : url Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97304
Titre : Introduction to scientific programming with Python Type de document : Guide/Manuel Auteurs : Joakim Sundnes, Auteur Editeur : Springer Nature Année de publication : 2020 Importance : 157 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-030-50356-7 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Langages informatiques
[Termes descripteurs IGN] équation polynomiale
[Termes descripteurs IGN] interface graphique
[Termes descripteurs IGN] programmation adaptée à l'objet
[Termes descripteurs IGN] Python (langage de programmation)Résumé : (éditeur) This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies. Note de contenu : 1- Getting started with Python
2- Computing with formulas
3- Loops and lists
4- Functions and branching
5- User input and error handling
6- Arrays and plotting
7- Dictionaries and strings
8- Classes
9- Object-oriented programmingNuméro de notice : 28555 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Manuel informatique DOI : 10.1007/978-3-030-50356-7 En ligne : https://doi.org/10.1007/978-3-030-50356-7 Format de la ressource électronique : url Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97444
Titre : Martin Waldseemüller’s carta marina of 1516 : Study and transcription of the long legends Type de document : Monographie Auteurs : Chet Van Duzer, Auteur Editeur : Springer Nature Année de publication : 2020 Importance : 150 p. ISBN/ISSN/EAN : 978-3-030-22703-6 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie ancienne
[Termes descripteurs IGN] carte ancienne
[Termes descripteurs IGN] carte marine
[Termes descripteurs IGN] histoire de la cartographie
[Termes descripteurs IGN] Renaissance
[Termes descripteurs IGN] seizième siècleRésumé : (éditeur) This open access book presents the first detailed study of one of the most important masterpieces of Renaissance cartography, Martin Waldseemüller’s Carta marina of 1516. By transcribing, translating into English, and detailing the sources of all of the descriptive texts on the map, as well as the sources of many of the images, the book makes the map available to scholars in a wholly unprecedented way. In addition, the book provides revealing insights into how Waldseemüller went about making the map (information that can’t be found in any other source). The Carta marina is the result of Waldseemüller’s radical re-evaluation of what a world map should be; he essentially started from scratch when he created it, rejecting the Ptolemaic model and other sources he had used in creating his 1507 map, and added more descriptive texts and a wealth of illustrations. Given its content, the book offers an essential reference work not only on this map, but also for anyone working in sixteenth-century European cartography. Note de contenu : 1- Introduction to the Carta Marina
2- The Long Legends: Transcription, Translation, and CommentaryNuméro de notice : 25981 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie DOI : 10.1007/978-3-030-22703-6 En ligne : https://doi.org/10.1007/978-3-030-22703-6 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96714 Nonparametric Bayesian learning for collaborative robot multimodal introspection / Xuefeng Zhou · (2020)
Titre : Nonparametric Bayesian learning for collaborative robot multimodal introspection Type de document : Monographie Auteurs : Xuefeng Zhou ·, Auteur ; Hongmin Wu, Auteur ; Juan Rojas, Auteur ; et al., Auteur Editeur : Springer Nature Année de publication : 2020 Importance : 137 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-981-1562631-- Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes descripteurs IGN] apprentissage automatique
[Termes descripteurs IGN] classification bayesienne
[Termes descripteurs IGN] inférence
[Termes descripteurs IGN] interface homme-machine
[Termes descripteurs IGN] modèle de Markov caché
[Termes descripteurs IGN] modèle mathématique
[Termes descripteurs IGN] problème de Dirichlet
[Termes descripteurs IGN] robotiqueRésumé : (éditeur) This open access book focuses on robot introspection, which has a direct impact on physical human–robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies. In robotics, the ability to reason, solve their own anomalies and proactively enrich owned knowledge is a direct way to improve autonomous behaviors. To this end, the authors start by considering the underlying pattern of multimodal observation during robot manipulation, which can effectively be modeled as a parametric hidden Markov model (HMM). They then adopt a nonparametric Bayesian approach in defining a prior using the hierarchical Dirichlet process (HDP) on the standard HMM parameters, known as the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The HDP-HMM can examine an HMM with an unbounded number of possible states and allows flexibility in the complexity of the learned model and the development of reliable and scalable variational inference methods. This book is a valuable reference resource for researchers and designers in the field of robot learning and multimodal perception, as well as for senior undergraduate and graduate university students. Note de contenu : 1- Introduction to robot introspection
2- Nonparametric Bayesian modeling of multimodal time series
3- Incremental learning robot task representation and identification
4- Nonparametric Bayesian method for robot anomaly monitoring
5- Nonparametric Bayesian method for robot anomaly diagnose
6- Learning policy for robot anomaly recovery based on robot introspectionNuméro de notice : 25965 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Monographie DOI : 10.1007%2F978-981-15-6263-1 En ligne : https://link.springer.com/book/10.1007%2F978-981-15-6263-1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96557
