Results 21 to 30 of about 6,980 (145)
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Comprehensive comparisons of gradient-based multi-label adversarial attacks
Adversarial examples which mislead deep neural networks by adding well-crafted perturbations have become a major threat to classification models. Gradient-based white-box attack algorithms have been widely used to generate adversarial examples.
Zhijian Chen +4 more
doaj +1 more source
Role of Structural Disorder on Phonon Transport and Thermal Conductivity in Li6PS5Br
Solid electrolytes are fast ion and slow heat conductors. Although both transport properties are governed by lattice dynamics and atomic structure, their interplay remains poorly understood. Here, we study this interrelation in anion‐ordered and disordered Li6PS5Br.
Lukas Ketter +4 more
wiley +1 more source
Self‐invalidating multilayer physical unclonable functions (PUFs) integrate fingerprint‐like metal nanopattern bilayers from block copolymer templates with highly reactive reduced graphene oxide (rGO) interlayers. This tamper‐responsive architecture blocks all unauthorized physical and chemical replication attempts while autonomously deactivating ...
Gyu Hui Jo +7 more
wiley +1 more source
Neuromorphic Devices and Computing for Sensing, Memory, and Control
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu +2 more
wiley +1 more source
Adversarial Robust and Explainable Network Intrusion Detection Systems Based on Deep Learning
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 +3 more
doaj +1 more source
scGEN combines attribute–structure encoding, adaptive hard‐sample weighting, and regularized zero‐inflated negative binomial loss to resolve ambiguous single‐cell states. In the developing human pituitary, refined annotations reveal Pre.Gonado cells at 7 weeks and previously obscured developmental communication networks.
Fang Huang +16 more
wiley +1 more source
Adversarial Attacks to Manipulate Target Localization of Object Detector
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 +7 more
doaj +1 more source
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
A dual‐randomness hardware platform is demonstrated by integrating PUF and TRNG functionalities into mixed‐ZGO nanoclusters. By leveraging spatial and temporal stochasticity, the mixed‐ZGO NCs device enables both unique identification and random signal generation.
Seungme Kang +6 more
wiley +1 more source

