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1. |
Record Nr. |
UNINA9910703366403321 |
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Autore |
Wohlgemuth J (John), <1946-> |
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Titolo |
Large-scale PV module manufacturing using ultra-thin polycrystalline silicon solar cells [[electronic resource] ] : annual subcontract report, 1 April 2002-30 September 2003 / / J. Wohlgemuth and S.P. Shea |
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Pubbl/distr/stampa |
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Golden, Colo. : , : National Renewable Energy Laboratory, , 2004 |
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Edizione |
[Rev. Apr. 2004.] |
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Descrizione fisica |
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1 online resource (viii, 45 pages) : illustrations |
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Collana |
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Altri autori (Persone) |
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Soggetti |
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Photovoltaic cells - Materials |
Solar cells - Materials |
Manufacturing processes |
Thin films |
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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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Title from title screen (viewed June 17, 2004). |
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Nota di bibliografia |
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Includes bibliographical references. |
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2. |
Record Nr. |
UNISA996464418803316 |
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Autore |
Gao Jie <1985-> |
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Titolo |
Connectivity and edge computing in IoT : customized designs and AI-based solutions / / Jie Gao, Mushu Li, Weihua Zhuang |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer, , [2021] |
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©2021 |
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ISBN |
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Descrizione fisica |
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1 online resource (177 pages) |
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Collana |
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Wireless networks (Springer (Firm)) |
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Disciplina |
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Soggetti |
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Internet of things |
Edge computing |
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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 and index. |
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Nota di contenuto |
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Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 Introduction -- 1.1 The Era of Internet of Things -- 1.2 Connectivity in IoT -- 1.3 Edge Computing in IoT -- 1.4 AI in IoT -- 1.5 Scope and Organization of This Book -- References -- 2 Industrial Internet of Things: Smart Factory -- 2.1 Industrial IoT Networks -- 2.2 Connectivity Requirements of Smart Factory -- 2.2.1 Application-Specific Requirements -- 2.2.2 Related Standards -- 2.2.3 Potential Non-Link-Layer Solutions -- 2.2.4 Link-Layer Solutions: Recent Research Efforts -- 2.3 Protocol Design for Smart Factory -- 2.3.1 Networking Scenario -- 2.3.2 Mini-Slot Based Carrier Sensing (MsCS) -- 2.3.3 Synchronization Sensing (SyncCS) -- 2.3.4 Differentiated Assignment Cycles -- 2.3.5 Superimposed Mini-slot Assignment (SMsA) -- 2.3.6 Downlink Control -- 2.4 Performance Analysis -- 2.4.1 Delay Performance with No Buffer -- 2.4.2 Delay Performance with Buffer -- 2.4.3 Slot Idle Probability -- 2.4.4 Impact of SyncCS -- 2.4.5 Impact of SMsA -- 2.5 Scheduling and AI-Assisted Protocol Parameter Selection -- 2.5.1 Background -- 2.5.2 The Considered Scheduling Problem -- 2.5.3 Device Assignment -- 2.5.4 AI-Assisted Protocol Parameter Selection -- 2.6 Numerical Results -- 2.6.1 Mini-Slot Delay with MsCS, SyncCS, and SMsA -- 2.6.2 Performance of the Device Assignment Algorithms -- 2.6.3 DNN-Assisted Scheduling -- 2.7 Summary -- References -- 3 UAV-Assisted Edge Computing: Rural IoT |
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Applications -- 3.1 Background on UAV-Assisted Edge Computing -- 3.2 Connectivity Requirements of UAV-Assisted MEC for Rural IoT -- 3.2.1 Network Constraints -- 3.2.2 State-of-the-Art Solutions -- 3.3 Multi-Resource Allocation for UAV-Assisted Edge Computing -- 3.3.1 Network Model -- 3.3.2 Communication Model -- 3.3.3 Computing Model -- 3.3.4 Energy Consumption Model -- 3.3.5 Problem Formulation. |
3.3.6 Optimization Algorithm for UAV-Assisted EdgeComputing -- 3.3.7 Proactive Trajectory Design Based on Spatial Distribution Estimation -- 3.4 Numerical Results -- 3.5 Summary -- References -- 4 Collaborative Computing for Internet of Vehicles -- 4.1 Background on Internet of Vehicles -- 4.2 Connectivity Challenges for MEC -- 4.2.1 Server Selection for Computing Offloading -- 4.2.2 Service Migration -- 4.2.3 Cooperative Computing -- 4.3 Computing Task Partition and Scheduling for Edge Computing -- 4.3.1 Collaborative Edge Computing Framework -- 4.3.2 Service Delay -- 4.3.3 Service Failure Penalty -- 4.3.4 Problem Formulation -- 4.3.5 Task Partition and Scheduling -- 4.4 AI-Assisted Collaborative Computing Approach -- 4.5 Performance Evaluation -- 4.5.1 Task Partition and Scheduling Algorithm -- 4.5.2 AI-Based Collaborative Computing Approach -- 4.6 Summary -- References -- 5 Edge-Assisted Mobile VR -- 5.1 Background on Mobile Virtual Reality -- 5.2 Caching and Computing Requirements of Mobile VR -- 5.2.1 Mobile VR Video Formats -- 5.2.2 Edge Caching for Mobile VR -- 5.2.3 Edge Computing for Mobile VR -- 5.3 Mobile VR Video Caching and Delivery Model -- 5.3.1 Network Model -- 5.3.2 Content Distribution Model -- 5.3.3 Content Popularity Model -- 5.3.4 Research Objective -- 5.4 Content Caching for Mobile VR -- 5.4.1 Adaptive Field-of-View Video Chunks -- 5.4.1.1 Extended FoV -- 5.4.1.2 Content Types -- 5.4.1.3 Rules for Content Distribution -- 5.4.2 Content Placement on an Edge Cache -- 5.4.3 Placement Scheme for Video Chunks in a VS -- 5.4.4 Placement Scheme for Video Chunks of Multiple VSs -- 5.4.5 Numerical Results -- 5.5 AI-Assisted Mobile VR Video Delivery -- 5.5.1 Content Distribution -- 5.5.2 Intelligent Content Distribution Framework -- 5.5.3 WI-based Delivery Scheduling -- 5.5.4 Reinforcement Learning Assisted Content Distribution. |
5.5.5 Neural Network Structure -- 5.5.6 Numerical Results -- 5.6 Summary -- References -- 6 Conclusions -- 6.1 Summary of the Research -- 6.2 Discussion of Future Directions -- Index. |
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