The transportation sector accounts for approximately 21% of global CO 2 emissions ( ≈ 8.4 Gt CO 2 in 2024), and the electrification of road transport is a critical lever for decarbonisation. Annual global EV battery deployment reached 1.2 TWh in 2025, making accurate battery health monitoring essential for both perform...
Subrahmanyam Tanala, Appalabathula Venkatesh· Next Sustainability· 0 citations
It is concluded that integrating FL with cross-chain blockchain technology can significantly enhance privacy, security, and collaboration among diverse AI systems, paving the way for next-generation decentralized intelligence.
Vikrant Thombare, Mahendra Sawane· International Journal of Cre...· 0 citations
A module-decomposition-driven SOC prediction model is proposed that separates baseline drain, synchronous state response, and asynchronous multi-scale event memory within one discharge-dynamics formulation and connects module-structured data processing, federated synthesis, few-shot adaptation, and local TTE inference...
This paper presents a novel approach to distributed machine learning, termed Federated Learning with Differential Privacy (FLDP), which addresses the critical challenge of privacy preservation in collaborative model training. Traditional federated learning techniques, while mitigating the risks associated with centrali...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
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The findings show that deep learning enhances aerial perception, reinforcement learning supports adaptive navigation and control, federated learning improves distributed intelligence, and swarm intelligence enables cooperative multi-UAV missions.
Binz A. Aziz, Mostafa A. Rushdi, Shigeo Yoshida et al.· Applied Sciences· 0 citations
This paper identifies key bottlenecks in technology deployment from a "Responsible AI" perspective and provides a theoretical framework and practical guidance for green AI and sustainable digital governance.
Zhen-Yu Lu· Advances in Engineering Inno...· 0 citations
Segmentation of medical images is a fundamental step towards quantification and clinical decision support. Many approaches have been proposed and successfully demonstrated on benchmark datasets. However, reliable application of current approaches in real clinical practice remains challenging. Medical image segmentation...
Sijia Zhu, Zhifang Sun, Juan Liao et al.· Discover Applied Sciences· 0 citations
The review combines recent research findings with guidance on new investigation tracks for developing all-encompassing AI systems which both spread far-reaching outcomes and follow sustainability requirements.
D. Usman· International Journal of Com...· 0 citations
Cloud computing has revolutionized the way computational resources are made available through scalable, flexible, and on-demand services. As promising as it is, efficient task scheduling remains an important challenge because of varied workloads, heterogeneous infrastructures, and multi-objective optimization requireme...
Federated learning (FL) presents a promising approach to training machine learning models on decentralized data sources while preserving user privacy. However, traditional FL methods often rely on a central server, introducing a single point of failure and potential privacy risks. This paper proposes a novel decentrali...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Federated learning (FL) is susceptible to poisoning attacks, where malicious clients manipulate local data or models to disrupt training. The system and data heterogeneity inherent in practical FL systems exacerbates these vulnerabilities, rendering existing defense mechanisms ineffective or infeasible. Specifically, d...
Peng Sun, Tao Liu, Yang Xu et al.· IEEE Transactions on Mobile...· 0 citations
This paper proposes a novel approach to decentralized federated learning (DFL) that leverages secure multi-party computation (SMPC) to guarantee data privacy during collaborative model training. Traditional federated learning methods, while promoting data sharing for model improvement, inherently expose individual data...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
