00982cam0 22002771 450 SOBE0002580320120531100218.020120531d1971 |||||ita|0103 baitaITEnglish Life and Customswith an appendix on the United StatesElo Chinol, Thomas FrankNapoliLiguori1971146 p.ill.23 cm.<Le >lingue e le civiltà straniere moderne001LAEC000168842001 Le *lingue e le civiltà straniere moderneChinol, ElioA60020003125507036264Frank, ThomasAF00013654070361440ITUNISOB20120531RICAUNISOBUNISOB82024375SOBE00025803M 102 Monografia moderna SBNM820000631SI24375rovitoUNISOBUNISOB20120531095557.020120531095613.0rovitoEnglish life and customs1203915UNISOB03577nam 2200517 450 99646640590331620230421124342.03-030-75452-910.1007/978-3-030-75452-5(CKB)4100000011951207(DE-He213)978-3-030-75452-5(MiAaPQ)EBC6635764(Au-PeEL)EBL6635764(OCoLC)1255219459(PPN)258852178(EXLCZ)99410000001195120720220125d2021 uy 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierMorphological models of random structures /Dominique Jeulin1st ed. 2021.Cham, Switzerland :Springer,[2021]©20211 online resource (XXXII, 919 p. 291 illus., 89 illus. in color.)Interdisciplinary Applied Mathematics,0939-6047 ;533-030-75451-0 1. Introduction -- Part I Tools for Random Structures -- 2 Introduction to Random Closed Sets and to Semi-continuous Random Functions -- 3 Quantitative Analysis of Random Structures -- Part II Models of Random Structures -- 4 Excursion sets of Gaussian RF -- 5 Stochastic Point Processes and Random Trees -- 6 Boolean Random Sets -- 7 Random Tessellations -- 8 The Mosaic Model -- 9 Boolean Random Functions -- 10 Random Tessellations and Boolean Random Functions -- 11 Dead Leaves Models: from Space Tessellations to Random Functions -- 12 Sequential Cox Boolean and Conditional Dead Leaves Models -- 13 Sequential Alternate Random Functions -- 14 Primary Grains and Primary Functions -- 15 Dilution Random Functions -- 16 Reaction-Diffusion and Lattice Gas Models -- 17 Texture Segmentation by Morphological Probabilistic Hierarchies -- Part III Random Structures and Change of Scale -- 18 Change of Scale in Physics of Random Media -- 19 Digital Materials -- 20 Probabilistic Models for Fracture Statistics -- 21 Crack Paths in Random Media.This book covers methods of Mathematical Morphology to model and simulate random sets and functions (scalar and multivariate). The introduced models concern many physical situations in heterogeneous media, where a probabilistic approach is required, like fracture statistics of materials, scaling up of permeability in porous media, electron microscopy images (including multispectral images), rough surfaces, multi-component composites, biological tissues, textures for image coding and synthesis. The common feature of these random structures is their domain of definition in n dimensions, requiring more general models than standard Stochastic Processes.The main topics of the book cover an introduction to the theory of random sets, random space tessellations, Boolean random sets and functions, space-time random sets and functions (Dead Leaves, Sequential Alternate models, Reaction-Diffusion), prediction of effective properties of random media, and probabilistic fracture theories.Interdisciplinary Applied Mathematics,0939-6047 ;53Random setsModels matemàticsthubLlibres electrònicsthubRandom sets.Models matemàtics519.2Jeulin D(Dominique),1076319MiAaPQMiAaPQMiAaPQBOOK996466405903316Morphological models of random structures2586700UNISA01080nam0 22002651i 450 UON0006204120231205102311.70920020107d1950 |0itac50 bagerUS|||| 1||||Anfangsgrunde der chinesischen Grammatik mit UbungstuckenGeorg von der GabelentzNew YorkFederick Ungar Publ. Co.1950VIII, 150 p., 1 c. di tav.23 cmLINGUA CINESEGRAMMATICHEUONC000763FIUSNew YorkUONL000050CIN II BCINA - LINGUISTICA - GRAMMATICHEADER_GABELENTZGeorg : vonUONV039529655646UngarUONV260782650ITSOL20240220RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00062041SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI CIN II B 062 SI MR 74377 5 062 Anfangsgrunde der chinesischen Grammatik mit Ubungstucken1173160UNIOR05336nam 22006135 450 991029922760332120240131142351.03-319-14142-210.1007/978-3-319-14142-8(CKB)3710000000404016(SSID)ssj0001500983(PQKBManifestationID)11885068(PQKBTitleCode)TC0001500983(PQKBWorkID)11521984(PQKB)10842328(DE-He213)978-3-319-14142-8(MiAaPQ)EBC6310757(MiAaPQ)EBC5588258(Au-PeEL)EBL5588258(OCoLC)907922612(PPN)185484743(EXLCZ)99371000000040401620150413d2015 u| 0engurnn#mmmmamaatxtccrData Mining The Textbook /by Charu C. Aggarwal1st ed. 2015.Cham :Springer International Publishing :Imprint: Springer,2015.1 online resource (XXIX, 734 p. 180 illus., 7 illus. in color.)Bibliographic Level Mode of Issuance: Monograph3-319-14141-4 Includes bibliographical references and index.Introduction to Data Mining -- Data Preparation -- Similarity and Distances -- Association Pattern Mining -- Association Pattern Mining: Advanced Concepts -- Cluster Analysis -- Cluster Analysis: Advanced Concepts -- Outlier Analysis -- Outlier Analysis: Advanced Concepts -- Data Classification -- Data Classification: Advanced Concepts -- Mining Data Streams -- Mining Text Data -- Mining Time-Series Data -- Mining Discrete Sequences -- Mining Spatial Data -- Mining Graph Data -- Mining Web Data -- Social Network Analysis -- Privacy-Preserving Data Mining.This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time series, discrete sequences, spatial data, graph data, and social networks. Until now, no single book has addressed all these topics in a comprehensive and integrated way. The chapters of this book fall into one of three categories: Fundamental chapters: Data mining has four main problems, which correspond to clustering, classification, association pattern mining, and outlier analysis. These chapters comprehensively discuss a wide variety of methods for these problems. Domain chapters: These chapters discuss the specific methods used for different domains of data such as text data, time-series data, sequence data, graph data, and spatial data. Application chapters: These chapters study important applications such as stream mining, Web mining, ranking, recommendations, social networks, and privacy preservation. The domain chapters also have an applied flavor. Appropriate for both introductory and advanced data mining courses, Data Mining: The Textbook balances mathematical details and intuition. It contains the necessary mathematical details for professors and researchers, but it is presented in a simple and intuitive style to improve accessibility for students and industrial practitioners (including those with a limited mathematical background). Numerous illustrations, examples, and exercises are included, with an emphasis on semantically interpretable examples. Praise for Data Mining: The Textbook - “As I read through this book, I have already decided to use it in my classes. This is a book written by an outstanding researcher who has made fundamental contributions to data mining, in a way that is both accessible and up to date. The book is complete with theory and practical use cases. It’s a must-have for students and professors alike!" -- Qiang Yang, Chair of Computer Science and Engineering at Hong Kong University of Science and Technology "This is the most amazing and comprehensive text book on data mining. It covers not only the fundamental problems, such as clustering, classification, outliers and frequent patterns, and different data types, including text, time series, sequences, spatial data and graphs, but also various applications, such as recommenders, Web, social network and privacy. It is a great book for graduate students and researchers as well as practitioners." -- Philip S. Yu, UIC Distinguished Professor and Wexler Chair in Information Technology at University of Illinois at Chicago.Data miningPattern perceptionData Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Pattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XData mining.Pattern perception.Data Mining and Knowledge Discovery.Pattern Recognition.006.312Aggarwal Charu Cauthttp://id.loc.gov/vocabulary/relators/aut518673MiAaPQMiAaPQMiAaPQBOOK9910299227603321Data Mining2497825UNINA