Results 71 to 80 of about 1,209,773 (317)

Nanozymes Integrated Biochips Toward Smart Detection System

Advanced Science, EarlyView.
This review systematically outlines the integration of nanozymes, biochips, and artificial intelligence (AI) for intelligent biosensing. It details how their convergence enhances signal amplification, enables portable detection, and improves data interpretation.
Dongyu Chen, Wang Zheng, Zhihui Zhang, Shenping Yu, Xinxin Hang, Han Wu, Xiao‐Wei Xiang, Wei Mu, Yanli Jiao, Zaizai Dong, Lingqian Chang   +10 more
wiley   +1 more source

Robust ConvLSTM Model With Deep Reinforcement Learning for Stealth Attack Detection in Smart Grids

IEEE Open Journal of the Industrial Electronics Society
The advent of modern electricity distribution systems, comprising digital communication technologies and principles, has triggered a new era of smart grids, in which advanced metering infrastructure plays a crucial role in functions, such as digital ...
Ahmad N. Alkuwari, Abdullatif Albaseer, Saif Al-Kuwari, Marwa Qaraqe   +3 more
doaj   +1 more source

Engineering Immune Cell to Counteract Aging and Aging‐Associated Diseases

Advanced Science, EarlyView.
This review highlights a paradigm shift in which advanced immune cell therapies, initially developed for cancer, are now being harnessed to combat aging. By engineering immune cells to selectively clear senescent cells and remodel pro‐inflammatory tissue microenvironments, these strategies offer a novel and powerful approach to delay age‐related ...
Jianhua Guo, Lanjie Lei, Ying Jin, Lan Su, Shumao Cui, Liyun Shi   +5 more
wiley   +1 more source

Multi-Stage Adversarial Defense for Online DDoS Attack Detection System in IoT

IEEE Access
Machine learning-based Distributed Denial of Service (DDoS) attack detection systems have proven effective in detecting and preventing DDoD attacks in Internet of Things (IoT) systems.
Yonas Kibret Beshah, Surafel Lemma Abebe, Henock Mulugeta Melaku   +2 more
doaj   +1 more source

A Robust Method to Protect Text Classification Models against Adversarial Attacks

Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022
Text classification is one of the main tasks in natural language processing. Recently, adversarial attacks have shown a substantial negative impact on neural network-based text classification models. There are few defenses to strengthen model predictions
BALA MALLIKARJUNARAO GARLAPATI, Ajeet Kumar Singh, Srinivasa Rao Chalamala   +2 more
doaj   +1 more source

In Situ Liquid‐Cell Transmission Electron Microscopy Insights Into Lithium‐Ion Battery Materials Degradation: Challenges and Emerging Solutions

Advanced Science, EarlyView.
Lithium‐ion battery degradation arises from complex, localized processes during operation, limiting long‐term performance. In situ electrochemical liquid cell TEM provides unique access to these mechanisms. This review summarizes degradation phenomena revealed by liquid cell TEM, traces the evolution of the three main cell designs, compares their ...
Walid Dachraoui, Rolf Erni
wiley   +1 more source

Breaking and Healing: GAN-Based Adversarial Attacks and Post-Adversarial Recovery for 5G IDSs

IEEE Access
Generative adversarial networks (GANs) have advanced rapidly in data augmentation and generation, and researchers have been exploring their applications in other areas, including adversarial attack generation.
Yasmeen Alslman, Mouhammd Alkasassbeh, Mohammad J. Abdel-Rahman   +2 more
doaj   +1 more source

Adversarial Robustness of Deep Reinforcement Learning Based Dynamic Recommender Systems

Frontiers in Big Data, 2022
Adversarial attacks, e.g., adversarial perturbations of the input and adversarial samples, pose significant challenges to machine learning and deep learning techniques, including interactive recommendation systems.
Siyu Wang, Yuanjiang Cao, Xiaocong Chen, Lina Yao, Xianzhi Wang, Quan Z. Sheng   +5 more
doaj   +1 more source

Attacking Adversarial Attacks as A Defense

, 2021
It is well known that adversarial attacks can fool deep neural networks with imperceptible perturbations. Although adversarial training significantly improves model robustness, failure cases of defense still broadly exist. In this work, we find that the adversarial attacks can also be vulnerable to small perturbations.
Wu, Boxi, Pan, Heng, Shen, Li, Gu, Jindong, Zhao, Shuai, Li, Zhifeng, Cai, Deng, He, Xiaofei, Liu, Wei   +8 more
openaire   +2 more sources

Urea‐Formaldehyde Resin Confined Silicon Nanodots Composites: High‐Performance and Ultralong Persistent Luminescence for Dynamic AI Information Encryption

Advanced Science, EarlyView.
Schematic illustration of SiNDs composite materials synthesis and its internal photophysical process mechanism. And an AI‐assisted dynamic information encryption process. ABSTRACT Persistent luminescence materials typically encounter an intrinsic trade‐off between high phosphorescence quantum yield (PhQY) and ultralong phosphorescence lifetime.
Yulu Liu, Lei Cao, Lele Gao, Panyong Wang, Qiannan You, Xinpei Pang, Li Li, Mingzheng Jia, Wen‐Fei Dong, Minghui Zan   +9 more
wiley   +1 more source