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▼a9789819621897▼9978-981-96-2189-7 |
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▼a10.1007/978-981-96-2189-7▼2doi |
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▼aWireless Sensor Networks▼h[electronic resource] :▼b18th China Conference, CWSN 2024, Taiyuan, China, September 20–22, 2024, Proceedings, Part II /▼cedited by Limin Sun, Yongle Chen. |
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▼a1st ed. 2025. |
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▼aSingapore :▼bSpringer Nature Singapore :▼bImprint: Springer,▼c2025. |
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▼aXXIII, 241 p. 102 illus., 94 illus. in color.▼bonline resource. |
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▼aCommunications in Computer and Information Science,▼x1865-0937 ;▼v2342 |
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▼a -- Smart Internet of Things. -- Semantic Information Enhancement and Semantic Alignment for Artistic Cross-Modal Retrieval. -- Dynamic Task Scheduling Strategy for Cloud-Edge Collaborative Environment. -- Mobility and Physical-Layer-Assissted Routing Protocol for UAV Networks in Jamming Environments. -- NNLoc: Enhancing COTS mmWave Localization with Neural Network. -- Efficient Visual Reinforcement Learning for IoT Control from Pixels. -- Dual-Channel Mixed Token Progressing Unit Model for Sign Language Production with Global Transformer and Local GCN. -- AI-Enhanced Forecasting in Telesurgery: When Machine Learning Meets Tactile Internet. -- A Distributed Software Framework for Vision-Based Drone Swarm Applications. -- Hybrid Unsupervised Time-series Anomaly Detection for Industrial IoT based on Spatiotemporal Feature. -- GAIN: Game-Theoretic Design of Fair Incentive Mechanisms for Multiple Model Owners in Federated Learning. -- Theory and Technology of Wireless Sensor Network. -- A Synthesis Library Subset Screening Method for High Energy Efficiency Requirements. -- An Optimization Strategy for Adaptive Wireless Sensor Networks Based on Compressed Sensing. -- Unmanned Vehicles Based Optimal RFID Inventory. -- ESC: Energy Savings Caching Scheme for Underwater Named Data Networking. -- Deep Reinforcement Learning-Based Joint Transmission Power and Channel Selection in UAV-Assisted Wireless Networks. -- A novel eLoran waveform based on linear frequency modulation. -- A Dynamic Privacy-awared Incentive Mechanism Based on Deep Reforcement Learning for Opportunistic Networks. -- TinyML-Based Approach for Dynamic Transmission Power in LoRaWAN Network. -- Resource Allocation for Reliable Transmission in IRS-Assisted Industrial Wireless Sensor Networks. |
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▼aThis two-volume set, CCIS 2341 and CCIS 2342, constitutes the refereed proceedings of the 18th China Conference on Wireless Sensor Networks, CWSN 2024, held in Taiyuan, China, during September 20–22, 2024. The 41 full papers presented in this volume were carefully reviewed and selected from 75 submissions. They were organized in topical sections as follows:- Part I: Cloud computing and edge computing; Internet of things security and privacy protection; Internet of things service and application technology. Part II: Smart internet of things; Theory and technology of wireless sensor network. |
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▼aComputer networks . |
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▼aComputers. |
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▼aImage processing▼xDigital techniques. |
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▼aComputer vision. |
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▼aApplication software. |
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▼aComputer Communication Networks. |
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▼aComputing Milieux. |
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▼aComputer Imaging, Vision, Pattern Recognition and Graphics. |
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▼aComputer and Information Systems Applications. |
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▼aSun, Limin.▼eeditor.▼4edt▼4http://id.loc.gov/vocabulary/relators/edt |
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▼aChen, Yongle.▼eeditor.▼4edt▼4http://id.loc.gov/vocabulary/relators/edt |
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▼tSpringer Nature eBook |
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▼iPrinted edition:▼z9789819621880 |
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▼iPrinted edition:▼z9789819621903 |
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▼aCommunications in Computer and Information Science,▼x1865-0937 ;▼v2342 |
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▼uhttps://doi.org/10.1007/978-981-96-2189-7 |
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▼aComputer Science (SpringerNature-11645) |
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▼aComputer Science (R0) (SpringerNature-43710) |