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Adversative and concessive conjunctions in EFL writing : corpus-based description and rhetorical structure analysis / / Yan Zhang
| Adversative and concessive conjunctions in EFL writing : corpus-based description and rhetorical structure analysis / / Yan Zhang |
| Autore | Zhang Yan |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XVI, 234 p. 42 illus., 18 illus. in color.) |
| Disciplina | 410 |
| Soggetto topico |
Linguistics
Comparative linguistics Language and languages - Study and teaching |
| ISBN | 981-15-7837-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Complexity of adversative and concessive conjunctions -- 2 A combined method of corpus-based and text-based analysis of adversative and concessive conjunctions -- 3 Adversative and concessive conjunctions: Comparing frequency distribution across two corpora -- 4 Analyzing structural conjunction but by investigating its co-occurrence patterns -- 5 Analyzing cohesive conjunction however by investigating its syntactic positions and agnation structures -- 6 Text-based analysis of adversative and concessive conjunctions -- 7 Conclusion. |
| Record Nr. | UNINA-9910484761303321 |
Zhang Yan
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| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Digital Twin : Architectures, Networks, and Applications / / by Yan Zhang
| Digital Twin : Architectures, Networks, and Applications / / by Yan Zhang |
| Autore | Zhang Yan |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (XVI, 126 p. 48 illus., 47 illus. in color.) |
| Disciplina | 620 |
| Collana | Simula SpringerBriefs on Computing |
| Soggetto topico |
Engineering mathematics
Engineering - Data processing Telecommunication Wireless communication systems Mobile communication systems Computer networks Artificial intelligence Machine learning Mathematical and Computational Engineering Applications Communications Engineering, Networks Wireless and Mobile Communication Computer Communication Networks Artificial Intelligence Machine Learning |
| ISBN | 3-031-51819-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: Introduction -- Chapter 2: Digital Twin Models and Networks -- Chapter 3: Artificial Intelligence for Digital Twin -- Chapter 4: Edge Computing for Digital Twin -- Chapter 5: Blockchain for Digital Twin -- Chapter 6: Digital Twin for 6G Networks -- Chapter 7: Digital Twin for Aerial-Ground Networks -- Chapter 8: Digital Twin for Internet of Vehicles. |
| Record Nr. | UNINA-9910829580503321 |
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Zhang Yan
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Mobile Edge Computing [[electronic resource]]
| Mobile Edge Computing [[electronic resource]] |
| Autore | Zhang Yan |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
| Descrizione fisica | 1 online resource (123 p.) |
| Collana | Simula SpringerBriefs on Computing |
| Soggetto topico |
Mobile & handheld device programming / Apps programming
WAP (wireless) technology Electrical engineering Computing & information technology |
| Soggetto non controllato |
Open Access
mobile edge computing 5G beyond 6G edge caching Internet of Things UAV |
| ISBN | 3-030-83944-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 Introduction -- 1.1 Mobile Cloud Computing (MCC) -- 1.2 Overview of MEC -- 1.3 Book Organization -- 2 Mobile Edge Computing -- 2.1 A Hierarchical Architecture of Mobile Edge Computing (MEC) -- 2.2 Computation Model -- 2.2.1 Computation Model of Local Execution -- 2.2.2 Computation Model of Full Offloading -- 2.2.3 A Computation Model for Partial Offloading -- 2.3 Offloading Policy -- 2.3.1 Binary Offloading -- 2.3.2 Partial Offloading -- 2.4 Challenges and Future Directions -- 3 Mobile Edge Caching -- 3.1 Introduction
3.2 The Architecture of Mobile Edge Caching -- 3.3 Caching Performance Metrics -- 3.3.1 Hit Rate Ratio -- 3.3.2 Content Acquisition Latency -- 3.3.3 Quality of Experience (QoE) -- 3.3.4 Caching System Utility -- 3.4 Caching Service Design and Data Scheduling Mechanisms -- 3.4.1 Edge Caching Based on Network Infrastructure Services -- 3.4.2 Edge Caching Based on D2D Services -- 3.4.3 Hybrid Service-Enabled Edge Caching -- 3.5 Case Study: Deep Reinforcement Learning-Empowered … -- 3.5.1 System Model -- 3.5.2 Problem Formulation and a DDPG-Based Optimal Content Dispatch Scheme 3.5.3 Numerical Results -- 4 Mobile Edge Computing for Beyond 5G/6G -- 4.1 Fundamental Characteristics of 6G -- 4.2 Integrating Mobile Edge Computing (MEC) … -- 4.2.1 Use Cases of Integrating MEC into 6G -- 4.2.2 Applications of Integrating MEC into 6G -- 4.2.3 Challenges of Integrating MEC into 6G -- 4.3 Case Study: MEC-Empowered Edge Model Sharing for 6G -- 4.3.1 Sharing at the Edge: From Data to Model -- 4.3.2 Architecture of Edge Model Sharing -- 4.3.3 Processes of Edge Model Sharing -- 5 Mobile Edge Computing for the Internet of Vehicles -- 5.1 Introduction -- 5.2 Challenges in VEC 5.3 Architecture of VEC -- 5.4 Key Techniques of VEC -- 5.4.1 Task Offloading -- 5.4.2 Heterogeneous Edge Server Cooperation -- 5.4.3 AI-Empowered VEC -- 5.5 A Case Study -- 5.5.1 Predictive Task Offloading for Fast-Moving Vehicles -- 5.5.2 Deep Q-Learning for Vehicular Computation Offloading -- 6 Mobile Edge Computing for UAVs -- 6.1 Unmanned Aerial Vehicle-Assisted Mobile Edge Computing (MEC) Networks -- 6.2 Joint Trajectory and Resource Optimization in UAV-Assisted MEC Networks -- 6.2.1 Resource Allocation and Optimization in the Scenario of a UAV Exploiting MEC Computing Capabilities 6.2.2 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Computing Server -- 6.2.3 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Relay for Computation Offloading -- 6.3 Case Study: UAV Deployment and Resource Optimization for MEC at a Wind Farm -- 6.3.1 UAV Deployment for MEC at a Wind Farm -- 6.3.2 Joint Trajectory and Resource Optimization of UAV-Aided MEC at a Wind Farm -- 6.4 Conclusions -- 7 The Future of Mobile Edge Computing -- 7.1 The Integration of Blockchain and Mobile Edge Computing (MEC) -- 7.1.1 The Blockchain Structure 7.1.2 Blockchain Classification |
| Record Nr. | UNISA-996464547003316 |
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Zhang Yan
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| Cham, : Springer International Publishing AG, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Mobile Edge Computing
| Mobile Edge Computing |
| Autore | Zhang Yan |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
| Descrizione fisica | 1 online resource (123 p.) |
| Collana | Simula SpringerBriefs on Computing |
| Soggetto topico |
Mobile & handheld device programming / Apps programming
WAP (wireless) technology Electrical engineering Computing & information technology |
| Soggetto non controllato |
Open Access
mobile edge computing 5G beyond 6G edge caching Internet of Things UAV |
| ISBN | 3-030-83944-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 Introduction -- 1.1 Mobile Cloud Computing (MCC) -- 1.2 Overview of MEC -- 1.3 Book Organization -- 2 Mobile Edge Computing -- 2.1 A Hierarchical Architecture of Mobile Edge Computing (MEC) -- 2.2 Computation Model -- 2.2.1 Computation Model of Local Execution -- 2.2.2 Computation Model of Full Offloading -- 2.2.3 A Computation Model for Partial Offloading -- 2.3 Offloading Policy -- 2.3.1 Binary Offloading -- 2.3.2 Partial Offloading -- 2.4 Challenges and Future Directions -- 3 Mobile Edge Caching -- 3.1 Introduction
3.2 The Architecture of Mobile Edge Caching -- 3.3 Caching Performance Metrics -- 3.3.1 Hit Rate Ratio -- 3.3.2 Content Acquisition Latency -- 3.3.3 Quality of Experience (QoE) -- 3.3.4 Caching System Utility -- 3.4 Caching Service Design and Data Scheduling Mechanisms -- 3.4.1 Edge Caching Based on Network Infrastructure Services -- 3.4.2 Edge Caching Based on D2D Services -- 3.4.3 Hybrid Service-Enabled Edge Caching -- 3.5 Case Study: Deep Reinforcement Learning-Empowered … -- 3.5.1 System Model -- 3.5.2 Problem Formulation and a DDPG-Based Optimal Content Dispatch Scheme 3.5.3 Numerical Results -- 4 Mobile Edge Computing for Beyond 5G/6G -- 4.1 Fundamental Characteristics of 6G -- 4.2 Integrating Mobile Edge Computing (MEC) … -- 4.2.1 Use Cases of Integrating MEC into 6G -- 4.2.2 Applications of Integrating MEC into 6G -- 4.2.3 Challenges of Integrating MEC into 6G -- 4.3 Case Study: MEC-Empowered Edge Model Sharing for 6G -- 4.3.1 Sharing at the Edge: From Data to Model -- 4.3.2 Architecture of Edge Model Sharing -- 4.3.3 Processes of Edge Model Sharing -- 5 Mobile Edge Computing for the Internet of Vehicles -- 5.1 Introduction -- 5.2 Challenges in VEC 5.3 Architecture of VEC -- 5.4 Key Techniques of VEC -- 5.4.1 Task Offloading -- 5.4.2 Heterogeneous Edge Server Cooperation -- 5.4.3 AI-Empowered VEC -- 5.5 A Case Study -- 5.5.1 Predictive Task Offloading for Fast-Moving Vehicles -- 5.5.2 Deep Q-Learning for Vehicular Computation Offloading -- 6 Mobile Edge Computing for UAVs -- 6.1 Unmanned Aerial Vehicle-Assisted Mobile Edge Computing (MEC) Networks -- 6.2 Joint Trajectory and Resource Optimization in UAV-Assisted MEC Networks -- 6.2.1 Resource Allocation and Optimization in the Scenario of a UAV Exploiting MEC Computing Capabilities 6.2.2 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Computing Server -- 6.2.3 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Relay for Computation Offloading -- 6.3 Case Study: UAV Deployment and Resource Optimization for MEC at a Wind Farm -- 6.3.1 UAV Deployment for MEC at a Wind Farm -- 6.3.2 Joint Trajectory and Resource Optimization of UAV-Aided MEC at a Wind Farm -- 6.4 Conclusions -- 7 The Future of Mobile Edge Computing -- 7.1 The Integration of Blockchain and Mobile Edge Computing (MEC) -- 7.1.1 The Blockchain Structure 7.1.2 Blockchain Classification |
| Record Nr. | UNINA-9910502647303321 |
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Zhang Yan
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| Cham, : Springer International Publishing AG, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Urban metabolism : theory, method and application / / Yan Zhang
| Urban metabolism : theory, method and application / / Yan Zhang |
| Autore | Zhang Yan |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (474 pages) |
| Disciplina | 359 |
| Soggetto topico | Urban ecology (Biology) |
| ISBN |
9789811991233
9789811991226 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | PART I Theory -- Chapter 1 Connotation of urban metabolism -- Chapter 2 Research progress of urban metabolism -- Chapter 3 Urban metabolism research framework -- PART II Method -- Chapter 4 Accounting evaluation of urban metabolism -- Chapter 5 Urban metabolism model simulation -- Chapter 6 Regulation of urban metabolism optimization -- PART III Application- Chapter 7 Material metabolism process analysis- Chapter 8 Energy metabolism process analysis -- Chapter 9 Analysis of carbon metabolism -- Chapter 10 Analysis of urban nitrogen metabolism process -- Chapter 11 Analysis of metabolic process in the park. |
| Record Nr. | UNINA-9910659479603321 |
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Zhang Yan
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| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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