Collaborative Computing: Networking, Applications and Worksharing [[electronic resource] ] : 19th EAI International Conference, CollaborateCom 2023, Corfu Island, Greece, October 4-6, 2023, Proceedings, Part II / / edited by Honghao Gao, Xinheng Wang, Nikolaos Voros

• Record Nr.: UNINA9910841862503321
• Autore: Gao Honghao
• Pubbl/distr/stampa: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
• ISBN: 9783031545283
• Edizione: [1st ed. 2024.]
• Descrizione fisica: 1 online resource (544 pages)
• Collana: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, , 1867-822X ; ; 562
• Altri autori (Persone): WangXinheng; VorosNikolaos
• Disciplina: 004.2
• Soggetti: Computer systems; Information storage and retrieval systems; Computer networks; Data protection; Software engineering; Computers, Special purpose; Computer System Implementation; Information Storage and Retrieval; Computer Communication Networks; Data and Information Security; Software Engineering; Special Purpose and Application-Based Systems
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Deep Learning and Application -- Task Offloading in UAV-to-Cell MEC Networks: Cell Clustering and Path Planning.LAMB: Label-induced Mixed-level Blending for Multimodal Multi-label Emotion Detection -- MSAM: Deep Semantic Interaction Network for Visual Question Answering -- Defeating the non-stationary opponent using deep reinforcement learning and opponent modeling -- Multi-agent Deep ; Reinforcement Learning-based Approach to Mobility-aware Caching -- D-AE: A Discriminant Encode-Decode Nets For Data Generation -- ECCRG: A Emotion- and Content-controllable Response Generation Model -- Origin-Destination Convolution Recurrent Network: A Novel OD Matrix Prediction Framework -- MD-TransUNet: TransUNet with Multi-Attention and Dilated Convolution for Brain Stroke Lesion Segmentation -- Graph Computing -- DGFormer: An Effective Dynamic Graph Transformer based Anomaly Detection Model for IoT Time Series -- STAPointGNN: Spatial-Temporal Attention Graph Neural Network for Gesture Recognition Using Millimeter-Wave Radar -- NPGraph: An Efficient Graph Computing Model in NUMA-Based Persistent Memory Systems -- tHR-Net: A Hybrid Reasoning Framework for Temporal Knowledge Graph -- Improving Code Representation Learning via Multi-view Contrastive Graph Pooling for Abstract Syntax Tree -- Security and Privacy Protection -- Protect applications and data in use in IoT environment using collaborative computing -- Robustness-enhanced assertion generation method based on code mutation and attack defense -- Secure Traffic Data Sharing in UAV-Assisted VANETs -- A Lightweight PUF-Based Group Authentication Scheme for Privacy-Preserving Metering Data Collection in Smart Grid -- A Semi-Supervised Learning Method for Malware Traffic Classification with Raw Bitmaps -- Secure and Private Approximated Coded Distributed Computing Using Elliptic Curve Cryptography -- A Novel Semi-supervised IoT Time Series Anomaly Detection Model using Graph Structure Learning -- Structural Adversarial Attack for Code Representation Models -- An Efficient Authentication and Key Agreement Scheme for CAV Internal Applications -- Processing and Recognition -- SimBPG: A comprehensive similarity evaluation metric for business process graphs -- Probabilistic Inference Based Incremental Graph Index for Similarity Search on Social Networks -- Cloud-Edge-Device Collaborative Image Retrieval and Recognition for Mobile Web -- Contrastive Learning-based Finger-Vein Recognition with Automatic Adversarial Augmentation -- Multi-Dimensional Sequential Contrastive Learning for QoS Prediction.
• Sommario/riassunto: The three-volume set LNICST 561, 562 563 constitutes the refereed post-conference proceedings of the 19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023, held in Corfu Island, Greece, during October 4-6, 2023. The 72 full papers presented in these proceedings were carefully reviewed and selected from 176 submissions. The papers are organized in the following topical sections: Volume I : Collaborative Computing, Edge Computing & Collaborative working, Blockchain applications, Code Search and Completion, Edge Computing Scheduling and Offloading. Volume II: Deep Learning and Application, Graph Computing, Security and Privacy Protection and Processing and Recognition. Volume III: Onsite Session Day 2, Federated learning and application, Collaborative working, Edge Computing and Prediction, Optimization and Applications.