HierFedPDP:Hierarchical federated learning with personalized differential privacy DOI

Sitong Li,

Yifan Liu,

Fan Feng

et al.

Journal of Information Security and Applications, Journal Year: 2024, Volume and Issue: 86, P. 103890 - 103890

Published: Sept. 19, 2024

Language: Английский

An effective and verifiable secure aggregation scheme with privacy-preserving for federated learning DOI
Rong Wang, Ling Xiong, Jiazhou Geng

et al.

Journal of Systems Architecture, Journal Year: 2025, Volume and Issue: unknown, P. 103364 - 103364

Published: Feb. 1, 2025

Language: Английский

Citations

1

Synchronization, Optimization, and Adaptation of Machine Learning Techniques for Computer Vision in Cyber-Physical Systems: A Comprehensive Analysis DOI Open Access

Kai Hung Tank,

Mohamed Chahine Ghanem, Vassil Vassilev

et al.

Published: Jan. 7, 2025

Cyber-Physical Systems (CPS) seamlessly integrate computers, networks, and physical devices, enabling machines to communicate, process data, respond real-world conditions in real-time. By bridging the digital worlds, CPS ensures operations that are efficient, safe, innovative, controllable. As smart cities autonomous become more prevalent, understanding is crucial for driving future progress. Recent advancements edge computing, AI-driven vision, collaborative systems have significantly enhanced capabilities. Synchronization, optimization, adaptation intricate processes impact performance across different domains. Therefore, identifying emerging trends uncovering research gaps essential highlight areas require further investigation improvement. A systematic review facilitates this by allowing researchers benchmark compare various techniques, evaluate their effectiveness, establish best practices. It provides evidence-based insights into optimal strategies implementation while addressing potential trade-offs performance, resource usage, reliability. Additionally, such reviews help identify widely accepted standards frameworks, contributing development of standardized approaches.

Language: Английский

Citations

0

Cyber-Physical Artificial Intelligence DOI Open Access
Sanghoon Lee, Jiyeong Chae,

Haewon Jeon

et al.

ACM Transactions on Cyber-Physical Systems, Journal Year: 2025, Volume and Issue: unknown

Published: March 6, 2025

The integration of Cyber-Physical Systems (CPS) and Artificial Intelligence (AI) presents both opportunities challenges. AI operates on the principle that “good things happen probabilistically,” while CPS adheres to “all bad must not happen,” requiring uncertainty-awareness. Furthermore, difference between AI’s resource accessibility assumption CPS’s limitations highlights need for resource-awareness. We introduce (CPAI), an interdisciplinary subfield research, address these constraints. To best our knowledge, CPAI is first research domain CPS-AI integration. propose a three-dimensional classification schema CPAI: Constraint (C),Purpose (P), Approach (A). also systematize process into 3 phases 9 steps. By analyzing 104 studies, we highlight key challenges insights from perspective. aims unify fragmented studies provide guidance reliable resource-efficient as component CPS.

Language: Английский

Citations

0

Research Progress on Processing Quality Traits and Suitable Varieties Selection of Edible mushrooms DOI Creative Commons
D. Yang, Lingli Li,

Qiaoping Zheng

et al.

Journal of Agriculture and Food Research, Journal Year: 2025, Volume and Issue: unknown, P. 101877 - 101877

Published: April 1, 2025

Language: Английский

Citations

0

HierFedPDP:Hierarchical federated learning with personalized differential privacy DOI

Sitong Li,

Yifan Liu,

Fan Feng

et al.

Journal of Information Security and Applications, Journal Year: 2024, Volume and Issue: 86, P. 103890 - 103890

Published: Sept. 19, 2024

Language: Английский

Citations

0