Results 101 to 110 of about 4,502,013 (256)

IGANEEG: an IoMT-enabled generative framework for small-sample schizophrenia EEG augmentation

Connection Science
In the Internet of Medical Things (IoMT), reliable electroencephalogram (EEG) analysis is crucial for early diagnosis of schizophrenia and other neurological disorders.
Xiaofeng Li, Heyan Huang, Yingjie Cai
doaj   +1 more source

Sample adaptive data augmentation with progressive scheduling

Data augmentation is a widely adopted technique utilized to improve the robustness of automatic speech recognition (ASR). Employing a fixed data augmentation strategy for all training data is a common practice. However, it is important to note that there
Lu, Hongxuan, Li, Biao
core  

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Sample-to-sample distances.

, 2018
Sample-to-sample distances.
Gottfried Martin (157401), David Conrad (4952032), Hansjürgen T. Agostini (739752), Günther Schlunck (42056), Bertan Cakir (4952029)   +4 more
core   +1 more source

Rapidly Solidified High‐Strength Invar 36 Prepared by Planar‐Flow Melt Spinning

Advanced Engineering Materials, EarlyView.
The Invar 36 alloy was rapidly solidified using the planar‐flow melt‐spinning technique. Ribbon samples with thicknesses ranging from 20 to 160 mm were produced. As the grain size of the ribbon decreased to sub‐micron levels, the hardness increased by more than 2 times.
Bekir Akgül, Mehmet Kul
wiley   +1 more source

On-Demand Augmentation for Long-Tail Data Through Subset- and Topic-Driven Sparsity Identification Framework

Data Science and Engineering
Large-scale, multi-dimensional mixed datasets are characterized by the pervasive "long-tail distribution." This phenomenon results in data sparsity in subspaces defined by multi-dimensional attribute combinations.
Kun Wu, Yaxi Hou, Shan Yang, Linlin Zhang, Nan Lu, Xiaosu Wang, Hanqi Zheng, Fei Ye, Zhenying He   +8 more
doaj   +1 more source

3D‐Printed Titanium Gyroid Scaffold Structure Integrated With Tough Hybrid Materials for Cartilage Replacement

Advanced Engineering Materials, EarlyView.
This study proposes a potential device design for joint cartilage replacement. Silica‐polytetrahydrofuran (SiO2‐PolyTHF) hybrids with customizable mechanical properties were developed to mimic the characteristics of a natural meniscus. These were synthesized through a two‐pot sol–gel hybrid process.
Yu‐Chien Lin, Gloria R. Young, Francesca Tallia, Reece N. Oosterbeek, Shaaz Ghouse, Edward Spiers, Nupur Kohli, Tom Briggs, Marc Masen, Siwei Li, Ren‐Jei Chung, Jonathan R. T. Jeffers, Julian R. Jones   +12 more
wiley   +1 more source

Unsupervised Domain Adaptation Algorithm for Time Series Based on Adaptive Contrastive Learning

Entropy
Time series data find extensive applications in finance, healthcare, and industrial monitoring domains. However, analytical models targeting such data are subject to notable constraints imposed by the rigid independent and identically distributed (IID ...
Huayong Liu, Peng Lin
doaj   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source

Biomass Native Structure Into Functional Carbon‐Based Catalysts for Fenton‐Like Reactions

Advanced Functional Materials, EarlyView.
This study indicates that eight biomasses with 2D flaky and 1D acicular structures influence surface O types, morphology, defects, N doping, sp2 C, and Co nanoparticles loading in three series of carbon, N‐doped carbon, and cobalt/graphitic carbon. This work identifies how these structural factors impact catalytic pathways, enhancing selective electron
Wenjie Tian, Jingkai Lin, Zhihao Tian, Selusiwe Ncube, Huayang Zhang, Emiliano Cortés, Hongqi Sun, Shaobin Wang   +7 more
wiley   +1 more source