Results 61 to 70 of about 5,879,357 (336)

Prefix Data Augmentation for Contrastive Learning of Unsupervised Sentence Embedding

open access: yesApplied Sciences
This paper presents prefix data augmentation (Prd) as an innovative method for enhancing sentence embedding learning through unsupervised contrastive learning.
Chunchun Wang, Shu Lv
doaj   +1 more source

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu   +10 more
wiley   +1 more source

Unsupervised Algorithms to Detect Zero-Day Attacks: Strategy and Application

open access: yesIEEE Access, 2021
In the last decade, researchers, practitioners and companies struggled for devising mechanisms to detect cyber-security threats. Among others, those efforts originated rule-based, signature-based or supervised Machine Learning (ML) algorithms that were ...
Tommaso Zoppi   +2 more
doaj   +1 more source

Next‐Generation Bio‐Reducible Lipids Enable Enhanced Vaccine Efficacy in Malaria and Primate Models

open access: yesAdvanced Functional Materials, EarlyView.
Structure–activity relationship (SAR) optimization of bio‐reducible ionizable lipids enables the development of highly effective lipid nanoparticle (LNP) mRNA vaccines. Lead LNPs show superior tolerability and antibody responses in rodents and primates, outperforming approved COVID‐19 vaccine lipids.
Ruben De Coen   +30 more
wiley   +1 more source

Using In Situ TEM to Understand the Surfaces of Electrocatalysts at Reaction Conditions: Single‐Atoms to Nanoparticles

open access: yesAdvanced Functional Materials, EarlyView.
This review summarizes recent advances in closed‐cell in situ TEM strategies for accurate determination of the activity and stability of single‐atom catalyst systems during operation. Operando conditions causing dynamic changes of SAC systems are highlighted and we explain why ensemble average‐based optical techniques may benefit from the technological
Martin Ek   +4 more
wiley   +1 more source

Convolutional Sparse Kernel Network for Unsupervised Medical Image Analysis

open access: yes, 2019
The availability of large-scale annotated image datasets and recent advances in supervised deep learning methods enable the end-to-end derivation of representative image features that can impact a variety of image analysis problems.
Ahn, Euijoon   +4 more
core   +1 more source

A Smart Magnetically Actuated Flip‐Disc Programmable Metasurface with Ultralow Power Consumption for Real‐Time Channel Control

open access: yesAdvanced Functional Materials, EarlyView.
The study proposes a 1‐bit programmable metasurface based on flip‐disc display, named flip‐disc metasurface (FD‐MTS). This new design enables ultralow energy consumption while maintaining coding patterns. It also exhibits high scalability and multifunctional flexibility.
Jiang Han Bao   +8 more
wiley   +1 more source

A Van der Waals Optoelectronic Synapse with Tunable Positive and Negative Post‐Synaptic Current for Highly Accurate Spiking Neural Networks

open access: yesAdvanced Functional Materials, EarlyView.
A van der Waals optoelectronic synaptic device based on a ReS2/WSe2 heterostructure and oxygen‐treated h‐BN is presented, which enables both positive and negative PSCs through photocarrier polarity reversal. Bidirectional plasticity arises from gate‐tunable band bending and charge trapping‐induced quasi‐doping.
Hyejin Yoon   +9 more
wiley   +1 more source

An Unsupervised Learning Approach to Condition Assessment on a Wound-Rotor Induction Generator

open access: yesEnergies, 2021
Accurate online diagnosis of incipient faults and condition assessment on generators is especially challenging to automate through supervised learning techniques, because of data imbalance.
Elsie Swana, Wesley Doorsamy
doaj   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

open access: yesAdvanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee   +17 more
wiley   +1 more source

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