Advanced Engineering Materials, EarlyView.Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley +1 more source
Advanced Engineering Materials, EarlyView.Herein, silicon‐based nanoparticle coatings on X2CrNiMo17‐12‐2 metal powder are presented. The coating process scale, process parameters, nanoparticle size (65–200 nm) as well as the coating amount are discussed regarding powder properties. The surface roughness affects the flowability, while reflectance depends on the coating material and surface ...
Arne Lüddecke +4 more
wiley +1 more source
The Significance of Machine Learning and its Applicability in The research Field [PDF]
The International Journal of Informatics, Media and Communication TechnologyThe last decade has seen a significant number of remarkable expansions in machine learning research. The field has achieved unprecedented popularity by developing new areas and increased momentum on the existing sites. Whereas the symbolic methods have
Sultan bin Saad Saud Al-Harbi
doaj +1 more source
Transfer Learning for Voice Activity Detection: A Denoising Deep Neural Network Perspective [PDF]
arXiv, 2013 Mismatching problem between the source and target noisy corpora severely hinder the practical use of the machine-learning-based voice activity detection (VAD). In this paper, we try to address this problem in the transfer learning prospective. Transfer learning tries to find a common learning machine or a common feature subspace that is shared by both ...
arxiv
Experimental Data Based Machine Learning Classification Models with Predictive Ability to Select in Vitro Active Antiviral and Non-Toxic Essential Oils [PDF]
, 2020 Manuela Sabatino +8 more
openalex +1 more source
Active resource partitioning and planning for storage systems using time series forecasting and machine learning techniques [PDF]
, 2021 Maher Amine Kachmar
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Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Advanced Engineering Materials, EarlyView.This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source
Online Active Learning of Reject Option Classifiers [PDF]
arXiv, 2019 Active learning is an important technique to reduce the number of labeled examples in supervised learning. Active learning for binary classification has been well addressed in machine learning. However, active learning of the reject option classifier remains unaddressed.
arxiv
Active learning for statistical phrase-based machine translation [PDF]
, 2009 Gholamreza Haffari +2 more
openalex +1 more source
Internal Temperature Evolution Metrology and Analytics in Li‐Ion Cells
Advanced Functional Materials, EarlyView.This study investigates the non‐linear evolution of internal temperatures across diverse operating conditions, highlighting the disparities between internal and external measurements and the resulting thermal asymmetries. The coupled thermo‐electrochemical modeling framework provides a comprehensive analysis of various heat generation modes, examining ...
Anuththara S. J. Alujjage +5 more
wiley +1 more source