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1. |
Record Nr. |
UNISA996280155203316 |
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Titolo |
IEEE standard for local and metropolitan area networks . Amendment 27 Enhancements to bridging of IEEE 802.11 media : bridges and bridged networks |
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Pubbl/distr/stampa |
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New York : , : IEEE, , 2016 |
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ISBN |
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Descrizione fisica |
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1 online resource (26 pages) |
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Disciplina |
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Soggetti |
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Local area networks (Computer networks) - Standards |
Metropolitan area networks (Computer networks) - Standards |
Computer networks - Security measures - Standards |
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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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Sommario/riassunto |
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Protocols, procedures, and managed objects to allow IEEE 802.11 media to provide internal connections within bridged networks, as well as access to bridged networks, are provided in this amendment. Scope: This standard specifies protocols, procedures, and managed objects to allow IEEE 802.11 media to provide internal connections within bridged networks, as well as access to bridged networks. |
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2. |
Record Nr. |
UNINA9911114448703321 |
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Autore |
Dao Nhu-Ngoc |
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Titolo |
Intelligence of Things : The Fourth International Conference on Intelligence of Things (ICIT 2025), Thailand, November 17-19, 2025, Proceedings. Volume 1 |
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Pubbl/distr/stampa |
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Cham : , : Springer, , 2026 |
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©2026 |
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ISBN |
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3-032-13102-2 |
9783032131027 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (0 pages) |
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Collana |
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Lecture Notes on Data Engineering and Communications Technologies Series ; ; v.281 |
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Altri autori (Persone) |
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Disciplina |
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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 contenuto |
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Lecture Notes on Data Engineering and Communications Technologies -- Intelligence of Things: Technologies and Applications -- Preface -- Organization -- Contents -- ML Optimized Reconfigurable Intelligent Surfaces for Efficient Wireless Energy Transmission in NOMA Systems -- IEP-WOCD: An Improved Whale Optimization Algorithm for Community Detection with Enhanced Population Diversity -- SSFAM: Applying Shallow-Level Attention Weights to Deep-Level Features in Breast Cancer Instance Segmentation -- RTFDD: A Robust Two-Stage Framework for Web Defacement Detection -- Accuracy-Improved Phase-System Using Regularized Linear-Fractional Programming and Bisection Search -- IDE: A Differential Evolution-Based Algorithm for Summarizing Multiple Vietnamese Comments -- An Effective Method for UAV LiDAR Point Cloud Data Segmentation Using SAL -- High-Precision Tomato Segmentation Using Lightweight Convolutional Architectures -- EBi-RRT: An Enhanced Bidirectional RRT via Target-Biased Sampling -- Classification of Facial Emotion of Students in Activities Using Deep Neural Networks -- Characterization of Nuisance Odors in a Veterinary Clinic Using Machine Learning -- AI-Driven IoT Wearable Devices for Remote Patient Monitoring -- QMAODV: A Q-Learning-Based Multipath Routing Protocol for UAV- |
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Enabled Ad Hoc IoT Networks -- Ensemble Machine Learning-Based Test Smell Prediction -- Dynamic Mobility Management in Fog Computing Architecture for IoT Applications -- FedFace: A Privacy-Preserving Self-Supervised Multi-task Federated Face Recognition System -- Performance of Modified Fractional Frequency Reuse Algorithm in Random Ultra Dense Networks -- Toward Robust Potato Leaf Disease Identification: Optimizing Performance via Comparative Feature Selection -- Environmental Performance of UAV Deployment in Rice-Based Agroecosystems: A Systematic Review. |
Lightweight CNN-Based Semantic Communication for Image Analysis -- Spectral Clustering for User-Item Graph Partitioning in Recommendation Systems -- Evaluating Sub-THz Hardware Impairments on 6G Waveforms Using various Modulation Techniques -- Hybrid CBLANet: An Efficient Framework for Stock Price Prediction -- Performance Evaluation of Tracking Filters for UAV Positioning Using 5G Signals in Urban Air Mobility Environments -- A Hybrid Autoencoder-Machine Learning Approach for Improved Orange Quality Assessment -- A Comparative Analysis of Clustering Algorithms for Speaker Diarization -- Reducing Real-World Sampling Time by Using Generative AI Agents for Synthesizing Data in IoT Anomaly Detection. |
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Sommario/riassunto |
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This book aims to provide state-of-the-art knowledge in the field of Intelligence of Things to both academic and industrial readers.In particular, undergraduate, graduate, and researchers may find valuable information to drive their future research. |
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