Results 51 to 60 of about 6,370 (239)

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Care and COVID 19: Lessons for liberals and neoliberals

Child &Family Social Work, EarlyView., 2023
Abstract Within the liberal political traditions, care is regarded as a private matter, a problem of ethics rather than justice. Social justice is framed as an issue of economics (re/distribution), culture (recognition) and/or politics (representation).
Kathleen Lynch
wiley   +1 more source

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

Adversarial Robust and Explainable Network Intrusion Detection Systems Based on Deep Learning

Applied Sciences, 2022
The ever-evolving cybersecurity environment has given rise to sophisticated adversaries who constantly explore new ways to attack cyberinfrastructure. Recently, the use of deep learning-based intrusion detection systems has been on the rise. This rise is
Kudzai Sauka, Gun-Yoo Shin, Dong-Wook Kim, Myung-Mook Han   +3 more
doaj   +1 more source

Ag/Ag2S Nanoparticle‐Based In‐Materio Lightweight Cryptographic System for IoT Edge Security

Advanced Intelligent Systems, EarlyView.
This work presents a nanomaterial‐based in materio encryption method that directly transforms analog signals through nonlinear Ag/Ag2S nanoparticle networks. By exploiting the inherently nonuniform characteristics that arise from random arrangement of nanoparticles as a unique security key, the approach produces highly complex encrypted waveforms ...
Hiroki Tabata, Yuma Yamashita, Yusuke Nakaoka, Oradee Srikimkaew, Muzhen Xu, Yuki Usami, Shunsuke Araki, Hirofumi Tanaka   +7 more
wiley   +1 more source

Adversarial Attacks to Manipulate Target Localization of Object Detector

IEEE Access
Adversarial attack has gradually become an important branch in the field of artificial intelligence security, where the potential threat brought by adversarial example attack is more not to be ignored.
Kai Xu, Xiao Cheng, Ji Qiao, Jia-Teng Li, Kai-Xuan Ji, Jia-Yong Zhong, Peng Tian, Jian-Xun Mi   +7 more
doaj   +1 more source

DTFA: Adversarial attack with discrete cosine transform noise and target features on deep neural networks

IET Image Processing, 2023
Image recognition on deep neural network is vulnerable to adversarial sample attacks. The adversarial attack accuracy is low when only limited queries on the target are allowed with the current black box environment.
Dong Yang, Wei Chen, Songjie Wei
doaj   +1 more source

Multi-Task Adversarial Attack

CoRR, 2020
Deep neural networks have achieved impressive performance in various areas, but they are shown to be vulnerable to adversarial attacks. Previous works on adversarial attacks mainly focused on the single-task setting. However, in real applications, it is often desirable to attack several models for different tasks simultaneously. To this end, we propose
Pengxin Guo 0001, Yuancheng Xu, Baijiong Lin, Yu Zhang 0006   +3 more
openaire   +2 more sources

Rethinking Classifier and Adversarial Attack

CoRR, 2022
Various defense models have been proposed to resist adversarial attack algorithms, but existing adversarial robustness evaluation methods always overestimate the adversarial robustness of these models (i.e., not approaching the lower bound of robustness). To solve this problem, this paper uses the proposed decouple space method to divide the classifier
Youhuan Yang, Lei Sun, Leyu Dai, Song Guo, Xiuqing Mao, Xiaoqin Wang, Bayi Xu   +6 more
openaire   +2 more sources

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

AI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury, Kandarpa Kumar Sarma, Lachit Dutta   +2 more
wiley   +1 more source