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Record Nr. |
UNINA9910829067703321 |
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Autore |
Behrens Mark <1975-> |
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Titolo |
Topological automorphic forms / / Mark Behrens, Tyler Lawson |
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Pubbl/distr/stampa |
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Providence, Rhode Island : , : American Mathematical Society, , 2009 |
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©2009 |
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ISBN |
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Descrizione fisica |
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1 online resource (167 p.) |
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Collana |
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Memoirs of the American Mathematical Society, , 0065-9266 ; ; Volume 204, Number 958 |
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Disciplina |
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Soggetti |
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Automorphic forms |
Algebraic topology |
Homotopy groups |
Shimura varieties |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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"Volume 204, Number 958 (second of 5 numbers)." |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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""Contents""; ""Abstract""; ""Introduction""; ""0.1. Background and motivation""; ""0.2. Subject matter of this book""; ""0.3. Organization of this book""; ""0.4. Acknowledgments""; ""Chapter 1. p-divisible groups""; ""1.1. Definitions""; ""1.2. Classification""; ""Chapter 2. The Honda-Tate classification""; ""2.1. Abelian varieties over finite fields""; ""2.2. Abelian varieties over Fp""; ""Chapter 3. Tate modules and level structures""; ""3.1. Tate modules of abelian varieties""; ""3.2. Virtual subgroups and quasi-isogenies""; ""3.3. Level structures""; ""3.4. The Tate representation"" |
""3.5. Homomorphisms of abelian schemes""""Chapter 4. Polarizations""; ""4.1. Polarizations""; ""4.2. The Rosati involution""; ""4.3. The Weil pairing""; ""4.4. Polarizations of B-linear abelian varieties""; ""4.5. Induced polarizations""; ""4.6. Classification of weak polarizations""; ""Chapter 5. Forms and involutions""; ""5.1. Hermitian forms""; ""5.2. Unitary and similitude groups""; ""5.3. Classification of forms""; ""Chapter 6. Shimura varieties of type U(1,n-1)""; ""6.1. Motivation""; ""6.2. Initial data""; ""6.3. Statement of the moduli problem"" |
""6.4. Equivalence of the moduli problems""""6.5. Moduli problems with |
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level structure""; ""6.6. Shimura stacks""; ""Chapter 7. Deformation theory""; ""7.1. Deformations of p-divisible groups""; ""7.2. Serre-Tate theory""; ""7.3. Deformation theory of points of Sh""; ""Chapter 8. Topological automorphic forms""; ""8.1. The generalized Hopkins-Miller theorem""; ""8.2. The descent spectral sequence""; ""8.3. Application to Shimura stacks""; ""Chapter 9. Relationship to automorphic forms""; ""9.1. Alternate description of Sh(Kp)""; ""9.2. Description of Sh(Kp)F""; ""9.3. Description of Sh(Kp)C"" |
""9.4. Automorphic forms""""Chapter 10. Smooth G-spectra""; ""10.1. Smooth G-sets""; ""10.2. The category of simplicial smooth G-sets""; ""10.3. The category of smooth G-spectra""; ""10.4. Smooth homotopy fixed points""; ""10.5. Restriction, induction, and coinduction""; ""10.6. Descent from compact open subgroups""; ""10.7. Transfer maps and the Burnside category""; ""Chapter 11. Operations on TAF""; ""11.1. The E-action of GU(Ap,)""; ""11.2. Hecke operators""; ""Chapter 12. Buildings""; ""12.1. Terminology""; ""12.2. The buildings for GL and SL""; ""12.3. The buildings for U and GU"" |
""Chapter 13. Hypercohomology of adele groups""""13.1. Definition of QGU and QU""; ""13.2. The semi-cosimplicial resolution""; ""Chapter 14. K(n)-local theory""; ""14.1. Endomorphisms of mod p points""; ""14.2. Approximation results""; ""14.3. The height n locus of Sh(Kp)""; ""14.4. K(n)-local TAF""; ""14.5. K(n)-local QU""; ""Chapter 15. Example: chromatic level 1""; ""15.1. Unit groups and the K(1)-local sphere""; ""15.2. Topological automorphic forms in chromatic filtration 1""; ""Bibliography""; ""Index"" |
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2. |
Record Nr. |
UNINA9910299279203321 |
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Titolo |
Multimedia Tools and Applications for Environmental & Biodiversity Informatics / / edited by Alexis Joly, Stefanos Vrochidis, Kostas Karatzas, Ari Karppinen, Pierre Bonnet |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
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ISBN |
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Edizione |
[1st ed. 2018.] |
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Descrizione fisica |
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1 online resource (XV, 221 p. 74 illus., 65 illus. in color.) |
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Collana |
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Multimedia Systems and Applications, , 2945-5715 |
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Disciplina |
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Soggetti |
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Multimedia systems |
Database management |
Artificial intelligence |
Environmental engineering |
Biotechnology |
Bioremediation |
Pattern recognition systems |
Multimedia Information Systems |
Database Management |
Artificial Intelligence |
Environmental Engineering/Biotechnology |
Automated Pattern Recognition |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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1 Introduction -- 2 Developing mobile applications for environmental and biodiversity citizen science: considerations and recommendations -- 3 A toolbox for understanding and implementing a citizens' observatory on air monitoring -- 4 A Real-Time Streaming and Detection System for Bio-acoustic Ecological Studies after the Fukushima Accident -- 5 Towards improved air quality monitoring using publicly available sky images -- 6 Traits: Structuring species information for discoverability, navigation and identification -- 7 Unsupervised Bioacoustic Segmentation by Hierarchical Dirichlet |
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Process Hidden Markov Model -- 8 Plant Identification: Experts vs. Machines in the Era of Deep Learning -- 9 Automated identification of herbarium specimens at different taxonomic levels -- 10 A deep learning approach to species distribution modelling -- A Existing Data and Metadata Standards and Schemas related to Citizen Science -- B Creative Commons (CC) and Open Data Commons (ODC) Licenses -- C List of Apps, Platforms and their Functionalities in Citizen Science Projects -- D Examples of Symbolic and Non-symbolic Rewards in Citizen Science Projects -- E List of Apps for Sonic Environment and Noise Pollution Monitoring. |
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Sommario/riassunto |
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This edited volume focuses on the latest and most impactful advancements of multimedia data globally available for environmental and earth biodiversity. The data reflects the status, behavior, change as well as human interests and concerns which are increasingly crucial for understanding environmental issues and phenomena. This volume addresses the need for the development of advanced methods, techniques and tools for collecting, managing, analyzing, understanding and modeling environmental & biodiversity data, including the automated or collaborative species identification, the species distribution modeling and their environment, such as the air quality or the bio-acoustic monitoring. Researchers and practitioners in multimedia and environmental topics will find the chapters essential to their continued studies. |
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