Cited by HierFedPDP:Hierarchical federated learning with personalized differential privacy

An effective and verifiable secure aggregation scheme with privacy-preserving for federated learning DOI

Rong Wang, Ling Xiong, Jiazhou Geng

и другие.

Journal of Systems Architecture, Год журнала: 2025, Номер unknown, С. 103364 - 103364

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

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

Kai Hung Tank,

Mohamed Chahine Ghanem, Vassil Vassilev

и другие.

Опубликована: Янв. 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.

Язык: Английский

Процитировано

Cyber-Physical Artificial Intelligence DOI

Sanghoon Lee, Jiyeong Chae,

Haewon Jeon

и другие.

ACM Transactions on Cyber-Physical Systems, Год журнала: 2025, Номер unknown

Опубликована: Март 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.

Язык: Английский

Процитировано

Research Progress on Processing Quality Traits and Suitable Varieties Selection of Edible mushrooms DOI