Buch, Englisch, 272 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 435 g
13th International Conference, NETYS 2025, Rabat, Morocco, May 21-23, 2025, Proceedings
Buch, Englisch, 272 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 435 g
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-032-00346-1
Verlag: Springer
This book constitutes the refereed proceedings of the 13th International Conference on Networked Systems, NETYS 2025, held in Rabat, Morocco, during May 21-23, 2025.
The 16 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 45 submissions.
They are grouped into the following topics: Verification; Distributed Systems; Machine Learning.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
.- Verification.
.- Reachability and Verification of Assertions for IoT Applications.
.- Enhancing Numerical Invariants Learning with Bounded Reachability Analysis.
.- Distributed Systems.
.- Distributed computation of temporal twins in periodic undirected time-varying graphs.
.- Verifying Parameterized Networks Specified by Vertex-Replacement Graph Grammars.
.- Secure Lineage Storage on Public and Private Blockchains.
.- Byzantine Fault-Tolerant Distributed Set Intersection with Redundancy and Its Relationship with Byzantine Optimization.
.- Pattern formation of mobile agents in dynamic grids.
.- An automaton model to succinctly represent suffix-based specifications of a concurrent system.
.- SmartShards: Churn-Tolerant Continuously Available Distributed Ledger.
.- On Restricting Separator Problems in the OBLOT Computational Landscape.
.- Machine Learning.
.- Going Forward-Forward in Distributed Learning.
.- An Ensemble Model for 30-Minute Blood Glucose Prediction in Type 1 Diabetes: Balancing Accuracy and Simplicity.
.- Networked LLM Agents: Toward Autonomous LLMs for Querying Heterogeneous Databases.
.- Plant Diseases Detection with Retrieval-Augmented Generation.
.- Impact of Sparsification and Quantization on Energy Consumption in Federated Learning.
.- Vgg-ViT: A Framework for Deepfakes Images Detection.
.- Heterogeneous Graph Neural Network Based Arabic Coreference Resolution.
