Results 91 to 100 of about 227,956 (276)

scPER: A Rigorous Computational Approach to Determine Cellular Subtypes in Tumors Aligned With Cancer Phenotypes From Total RNA Sequencing

Advanced Science, EarlyView.
scPER presents an adversarial‐autoencoder framework that deconvolves bulk total RNA‐seq to quantify tumor‐microenvironment cell types and uncover phenotype‐linked subclusters. Across diverse benchmarks, scPER improves accuracy over existing tools.
Bingrui Li, Xiaobo Zhou, Raghu Kalluri
wiley   +1 more source

Deformation Prediction of 4D‐Printed Active Composite Structures Based on Data Mining

Advanced Science, EarlyView.
A curvature‐driven sequence point generation (CSPG) algorithm based on data mining is proposed to predict the deformation of double‐layer voxelized composite structures of arbitrary lengths. In addition, the CSPG algorithm is applied to predict the deformation of 2D and 3D structures assembled from beam elements, and its effectiveness is validated ...
Mengtao Wang, Yifan Xu, Zaiyang Liu, Hidemitsu Furukawa, Zhongkui Wang, Ren Xu, Lin Meng   +6 more
wiley   +1 more source

Adversarial Neural Network Training for Secure and Robust Brain-to-Brain Communication

IEEE Access
In the rapidly evolving domain of brain-to-brain communication, safeguarding the transmission of information against adversarial threats is paramount.
Hossein Ahmadi, Ali Kuhestani, Luca Mesin   +2 more
doaj   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

Intelligent Sensing: The Emerging Integration of Machine Learning and Soft Sensors Based on Hydrogels and Ionogels

Advanced Science, EarlyView.
By integrating with machine learning (ML), hydrogel‐ and ionogel‐based soft sensors are gaining human brain‐like capabilities to perceive, learn, and predict. This review summarizes their advances, focusing on ML‐powered applications such as handwriting/gesture/object/motion/speech recognition, health monitoring, food detection, and beyond.
Wenqing He, Rumin Lin, Suixiu Kong, Mengyi Qiang, Lingqi Huang, Bing Dai, Xi Yao, Lei Su, Xueji Zhang   +8 more
wiley   +1 more source

Fortify Machine Learning Production Systems: Detect and Classify Adversarial Attacks [PDF]

, 2021
Matthew Ciolino, Josh Kalin, David Noever   +2 more
openalex   +1 more source

Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency

Advanced Energy Materials, EarlyView.
This perspective highlights how machine learning accelerates sustainable energy materials discovery by integrating quantum‐accurate interatomic potentials with property prediction frameworks. The evolution from statistical methods to physics‐informed neural networks is examined, showcasing applications across batteries, catalysts, and photovoltaics ...
Kwang S. Kim
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

Real-time, Universal, and Robust Adversarial Attacks Against Speaker Recognition Systems [PDF]

, 2020
Yi Xie, Cong Shi, Zhuohang Li, Jian Liu, Yingying Chen, Bo Yuan   +5 more
openalex   +1 more source

Digital Twin of Solid Oxide Electrochemical Cells: From 3D Microstructure Reconstruction to Multiphysics Modeling

Advanced Energy Materials, EarlyView.
This review outlines the implementation of digital twin frameworks for solid oxide electrochemical cells (SOCs), encompassing 3D microstructure reconstruction, quantitative morphological analysis, and microstructure‐resolved multiphysics modeling. Emphasis is placed on recent advances that position digital twins as powerful tools for microstructure ...
Seungsoo Jang, Yejin Kang, Kyung Taek Bae, Seong Hyun Park, Young Je Park, Dongyeon Kim, Hyeongmin Yu, Hyunjin Kim, Siwon Yu, Kang Taek Lee   +9 more
wiley   +1 more source