Muutke küpsiste eelistusi

E-raamat: Collaborative Computing: Networking, Applications and Worksharing: 18th EAI International Conference, CollaborateCom 2022, Hangzhou, China, October 15-16, 2022, Proceedings, Part II

Edited by , Edited by , Edited by , Edited by
  • Formaat - PDF+DRM
  • Hind: 110,53 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

The two-volume set LNICST 460 and 461 constitutes the proceedings of the 18th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2022, held in Hangzhou, China, in October 2022. 

The 57 full papers presented in the proceedings were carefully reviewed and selected from 171 submissions. The papers are organized in the following topical sections: Recommendation System; Federated Learning and application; Edge Computing and Collaborative working; Blockchain applications; Security and Privacy Protection; Deep Learning and application; Collaborative working; Images processing and recognition.
Security and Privacy Protection.- A Novel Risk Assessment Method Based
on Hybrid Algorithm for SCADA.- A Visual Tool for Interactively Privacy
Analysis and Preservation on Order-Dynamic Tabular Data.- Prevention of
GAN-based Privacy Inferring Attacks towards Federated Learning.- ACS: An
Efficient Messaging System With Strong Tracking-resistance.- Anti-Clone: A
Lightweight Approach for RFID Cloning Attacks Detection.- A
Privacy-Preserving Lightweight Energy Data Sharing Scheme based on Blockchain
for Smart Grid.- Dynamic Trust-Based Resource Allocation Mechanism for Secure
Edge Computing.- A Stochastic Gradient Descent Algorithm Based on Adaptive
Differential Privacy.- Evading Encrypted Traffic Classifiers by
Transferable Adversarial Traffic.- A Secure Auction Mechanism for Task
Allocation in Mobile Crowdsensing.- Deep Learning and application.- A
Pareto-EfficientTask-Allocation Framework based on Deep Reinforcement
Learning Algorithm in MEC.- An Adaptive Ensembled Neural Network-based
Approach to IoT Device Identification.- Fine-grained Head Pose Estimation
Based on 6D Rotation Representation with Multiregression Loss.- Purpose
Driven Biological Lawsuit Modeling and Analysis Based on DIKWP.- Research on
Depth-adaptive Dual-arm Collaborative Grasping Method.- Collaborative
working.- Semantic SLAM for mobile robot with Human-In-the-Loop.
-Incorporating Feature Labeling into Crowdsourcing for More Accurate
Aggregation Labels.- Cost Performance Driven Multi-Request Allocation in D2D
Service Provision Systems.- Collaborative Mobile Edge Computing through
UPF Selection.- Deep Reinforcement Learning for Multi-UAV Exploration under
Energy Constraints.- Optimization of Large-Scale Knowledge Forward Reasoning
Based on OWL 2 DL Ontology.- ITAR:A Method for Indoor RFID Trajectory
Automatic Recovery.- A Longitudinal Measurement and Analysis of Pink,
a Hybrid P2P IoT Botnet.- VT-GAT: A Novel VPN Encrypted Traffic
Classification Model Based on Graph Attention Neural Network.- Images
processing and recognition.- Landmark Detection Based on Human
Activity Recognition for Automatic Floor Plan Construction.- Facial Action
Unit Detection by exploring the weak relationships between AU labels.- An
improved dual-subnet lane line detection model with a channel attention
mechanism for complex environments.- Facial Expression Recognition Based on
Deep Spatiotemporal Attention Network.