Results 131 to 140 of about 98,849 (283)

Separated and Independent Contrastive Semi-Supervised Learning for Imbalanced Datasets

IEEE Access
Conventional semi-supervised learning (SSL) encounters challenges in effectively addressing issues associated with long-tail datasets, primarily stemming from imbalances within a dataset.
Dongyoung Kim, Won-Sook Lee, Young-Woong Ko, Jeong-Gun Lee   +3 more
doaj   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Advancing Research on Biomaterials and Biological Materials with Scanning Electron Microscopy under Environmental and Low Vacuum Conditions

Advanced Engineering Materials, EarlyView.
Herein, environmental scanning electron microscopy (ESEM) is discussed as a powerful extension of conventional SEM for life sciences. By combining high‐resolution imaging with variable pressure and humidity, ESEM allows the analysis of untreated biological materials, supports in situ monitoring of hydration‐driven changes, and advances the functional ...
Jendrian Riedel, Lea Dierker, Antoine Eyram Kwame, Kim Nora Wagner, Jonas J. Unterholzner, Jan‐Henning Dirks, Dorothea Brüggemann   +6 more
wiley   +1 more source

A Novel Transformer-Based Self-Supervised Learning Method to Enhance Photoplethysmogram Signal Artifact Detection

IEEE Access
Recent research has revealed that traditional machine learning methods, such as semi-supervised label propagation and K-nearest neighbors, outperform Transformer-based models in artifact detection from photoplethysmogram (PPG) signals, mainly when data ...
Thanh-Dung Le, Clara Macabiau, Kevin Albert, Philippe Jouvet, Rita Noumeir   +4 more
doaj   +1 more source

Nanoindentation Criteria for Combinatorial Thin Film Libraries

Advanced Engineering Materials, EarlyView.
Thin‐film material libraries are compositional spreads used for screening composition‐structure‐property relationships. Nanoindentation is often used to characterize mechanical behavior across these systems, however variations in methodology are widespread.
Andre Bohn, Adie Alwen, Andrea M. Hodge
wiley   +1 more source

Text-Guided Contrastive Mamba for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral image (HSI) classification is challenging due to their high spectral complexity and the need to model long-range dependencies. Although contrastive learning has shown promise, most existing approaches rely on convolutional neural networks ...
Baokai Zu, Zhengrui Yang, Yafang Li, Hongyuan Wang, Jianqiang Li, Ziping He   +5 more
doaj   +1 more source

Effect of Laser Deoxidation on Adhesive‐Bonded Aluminum in an Oxygen‐Free Atmosphere

Advanced Engineering Materials, EarlyView.
This study investigates laser ablation of aluminum under oxygen‐free conditions. The goal is to produce oxide‐free substrates that enable improved adhesive bonding with epoxy. Optimized laser parameters (90% overlap, 300 µJ) combined with oxide‐free substrates result in the highest tensile strength of the adhesive bond.
Sandra Gerland, Finn‐Lennard Janthur, Sarah Seffer, Jörg Hermsdorf, Ludger Overmeyer, Annika Raatz   +5 more
wiley   +1 more source

A Comparative Study of Contemporary Learning Paradigms in Bug Report Priority Detection

IEEE Access
The increasing complexity of software development demands efficient automated bug report priority classification, and recent advancements in deep learning hold promise. This paper presents a comparative study of contemporary learning paradigms, including
Eyup Halit Yilmaz, Ismail Hakki Toroslu, Omer Koksal   +2 more
doaj   +1 more source

ArieL : Adversarial Graph Contrastive Learning

ACM Transactions on Knowledge Discovery from Data
Contrastive learning is an effective unsupervised method in graph representation learning. The key component of contrastive learning lies in the construction of positive and negative samples. Previous methods usually utilize the proximity of nodes in the graph as the principle.
Shengyu Feng, Baoyu Jing, Yada Zhu, Hanghang Tong   +3 more
openaire   +3 more sources