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[null,"1.","Record Nr.",null,"UNINA9910558492703321"]
[null,null,"Autore",null,"Kim Haesik"]
[null,null,"Titolo",null,"Artificial intelligence for 6G / / Haesik Kim"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer International Publishing, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"9783030950415"]
[{"$nulls":4},"9783030950408"]
[null,null,"Descrizione fisica",null,"1 online resource (534 pages)"]
[null,null,"Disciplina",null,"621.384"]
[null,null,"Soggetti",null,"Wireless communication systems - Design and construction"]
[{"$nulls":4},"Wireless communication systems - Economic aspects"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Contents -- Abbreviations -- Part I Artificial Intelligence Techniques -- 1 Historical Sketch of Artificial Intelligence -- 1.1 Introduction to Artificial Intelligence -- 1.2 History of Artificial Intelligence -- References -- 2 Artificial Intelligence Ecosystem, Techniques, and Use Cases -- 2.1 Artificial Intelligence Ecosystem -- 2.2 Hardware and Software of Artificial Intelligence -- 2.3 Artificial Intelligence Techniques and Selection -- 2.4 Artificial Intelligence Workflow and Use Cases -- References -- 3 Unsupervised Learning -- 3.1 Types and Performance Metrics of Unsupervised Learning -- 3.2 Clustering Algorithms -- 3.2.1 Hierarchical Clustering -- 3.2.2 Partitional Clustering -- 3.3 Association Rule Mining -- 3.4 Dimensionality Reduction -- 3.5 Problems -- References -- 4 Supervised Learning -- 4.1 Supervised Learning Workflow, Metrics, and Ensemble Methods -- 4.2 Classification of Supervised Learning -- 4.2.1 Decision Tree -- 4.2.2 K-Nearest Neighbours -- 4.2.3 Support Vector Machine -- 4.3 Regression of Supervised Learning -- 4.3.1 Linear Regression -- 4.3.2 Gradient Descent Algorithms -- 4.3.3 Logistic Regression -- 4.4 Problems -- References -- 5 Reinforcement Learning -- 5.1 Introduction to Reinforcement Learning and Markov Decision Process -- 5.2 Model-Based Approaches -- 5.2.1 Policy Iteration -- 5.2.2 Value Iteration -- 5.3 Model-Free Approaches -- 5.3.1 Monte Carlo Methods -- 5.3.2 Temporal difference learning methods -- 5.4 Problems -- References -- 6 Deep Learning -- 6.1 Introduction to Deep Learning -- 6.2 Deep Neural Network -- 6.3 "]
[{"$nulls":4},"Convolutional Neural Network -- 6.4 Recurrent Neural Network -- 6.5 Problems -- References -- Part II AI-Enabled Communications and Networks Techniques for 6G -- 7 6G Wireless Communications and Networks Systems -- 7.1 6G Wireless Communications and Networks."]
[{"$nulls":4},"7.1.1 6G Use Cases and Requirements -- 7.1.2 6G Timeline, Technical Requirements, and Technical Challenges -- 7.1.3 6G Key Enabling Techniques -- 7.2 AI-Enabled 6G Wireless Communications and Networks -- 7.2.1 AI and ML Contributions to Physical Layers -- 7.2.2 AI and ML Contribution to Data Link and Network Layers and Open Research Challenges -- 7.3 Problems -- References -- 8 AI-Enabled Physical Layer -- 8.1 Design Approaches of AI-Enabled Physical Layer -- 8.2 End-To-End Physical Layer Redesign with Autoencoder -- 8.3 Wireless Channel Models -- 8.4 Signal Detection and Modulation -- 8.5 Channel Estimation -- 8.6 Error Control Coding -- 8.7 MIMO -- 8.8 Problems -- References -- 9 AI-Enabled Data Link Layer -- 9.1 Design Approaches of AI-Enabled Data Link Layer -- 9.2 Radio Resource Allocation and Scheduling -- 9.2.1 Resource Allocation Problems in Wireless Networks and Convex Optimization -- 9.2.2 Resource Allocation Models and Performance Measure -- 9.2.3 Utility Functions and Fairness of Resource Allocation -- 9.2.4 Resource Allocation Using AI Techniques -- 9.3 Handover Using AI Techniques -- 9.4 Problems -- References -- 10 AI-Enabled Network Layer -- 10.1 Design Approaches of AI-Enabled Network Layer -- 10.2 Cellular Systems and Networking -- 10.2.1 Evolution of Cellular Networks -- 10.2.2 Concept of Cellular Systems -- 10.2.3 Cell Planning -- 10.3 Network Traffic Prediction -- 10.3.1 Classic Network Traffic Prediction -- 10.3.2 AI-Enabled Network Traffic Prediction -- 10.4 Problems -- References -- Index."]
[null,"2.","Record Nr.",null,"UNINA9910688483903321"]
[null,null,"Titolo",null,"Birds : challenges and opportunities for business, conservation and research / / edited by Heimo Mikkola"]
[null,null,"Pubbl/distr/stampa",null,"London : , : IntechOpen, , 2021"]
[null,null,"Descrizione fisica",null,"1 online resource (168 pages)"]
[null,null,"Disciplina",null,"571.18"]
[null,null,"Soggetti",null,"Birds - Adaptation"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","For many humans, birds are the most fascinating group of animals and they are definitely among the best-known and studied organisms. Thanks to global citizen science data, we know that there are some 50 billion individual birds in the world at present, which is about six birds for every human on the planet. Birds have an important role as indicators of the state of the environment, giving them high public value. Human-related global impacts such as climate changes and accelerating urbanization force extant species to continuous adaptations, population modifications, or even outright extinction. This book includes nine chapters covering such topics as bird genetics, the colour of avian plumage, conservation problems, sustainable hunting, habitat disturbance, range expansion and introductions, and long-term bird population changes and challenges. A key chapter explains the genetic rules and reasons why we have continuously more bird species in the world and why we may end up having 7,000 species more than the present 11,000 species."]
[null,"3.","Record Nr.",null,"UNINA9910798093803321"]
[null,null,"Autore",null,"Ross Fiona <1966->"]
[null,null,"Titolo",null,"Dining with the famous and infamous / / Fiona Ross"]
[null,null,"Pubbl/distr/stampa",null,"Lanham, Maryland : , : Rowman & Littlefield, , 2016"]
[{"$nulls":4},"©2016"]
[null,null,"ISBN",null,"1-4422-5226-X"]
[null,null,"Descrizione fisica",null,"1 online resource (259 p.)"]
[null,null,"Collana",null,"Dining with Destiny Series"]
[null,null,"Disciplina",null,"641.5"]
[null,null,"Soggetti",null,"Cooking"]
[{"$nulls":4},"Celebrities"]
[{"$nulls":4},"Antiheroes"]
[{"$nulls":4},"Food habits - History"]
[{"$nulls":4},"Food in popular culture - History"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,null,"Sommario/riassunto","From Salvador Dali to Joan Crawford, Liz Taylor to Bob Dylan, the dining habits and preferences of celebrities, artists, movie stars, and the famous for being famous are revealed in this vivid and entertaining romp through the favored meals and snacks of famous, or infamous, figures throughout history."]