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Academic Articles & Research Papers
Showing 20 of 3,028 academic articles
Mathieu Calvat, Chris Bean, Dhruv Anjaria, Hyoungryul Park et al. • npj Computational Materials
(2025)
Abstract To leverage advancements in machine learning for metallic materials design and property prediction, it is crucial to develop a data-reduced representation of metal microstructures that surpasses the limitations of current physics-b...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41524-025-01770-8
Sun Ping • Materials Research Express
(2026)
Polymer solar cells (PSCs) rely on labor-intensive trial-and-error experiments to optimize power conversion efficiency (PCE), due to complex coupling of molecular electronic properties, blend morphology and fabrication parameters. This work...
DOAJ
Open Access (DOAJ)
DOI: 10.1088/2053-1591/aeaacc
Xiaoming Wu, Jingxuan Chang, Chengcheng Long, Hamzeh Ghorbani • Journal of Big Data
(2026)
Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s40537-026-01475-9
Meghna Chaudhary, Kristin Kosyluk, Sylvia Thomas, Tempestt Neal • Scientific Reports
(2023)
Abstract According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rate...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-023-37592-1
Binfang Hu, Chunhua Zhang, Baijun Chu, Peishan Gu et al. • Food Chemistry: X
(2023)
Key aroma components of 33 fragrant peanut oils with different aroma types were screened by combined using flavoromics and machine learning. A total of 108 volatile compounds were identified and 100 kinds of them were accurately quantified,...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.fochx.2023.100880
Yunji Chen, Tao Luo, Shaoli Liu, Shijin Zhang et al. • IEEE/ACM International Symposium on Microarchitecture (MICRO)
(2014)
Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learni...
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DOI: https://doi.org/10.1109/micro.2014.58
Phil Kim • Apress eBooks
(2017)
However, experts generally distinguish them. If you have decided to study this field, it’s important you understand what these words actually mean, and more importantly, how they differ. These keywords were added by machine and not by the a...
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DOI: https://doi.org/10.1007/978-1-4842-2845-6_1
Romulus Costache, Hazem Ghassan Abdo, Arun Pratap Mishra, Subodh Chandra Pal et al. • Geomatics, Natural Hazards & Risk
(2023)
AbstractIn this work, the vulnerability to flooding in the Prahova River basin was calculated and analyzed using advanced methods and techniques. Thus, 2 hybrid models represented by Iterative Classifier Optimizer – Multiclass Alternating D...
DOAJ
Open Access (DOAJ)
DOI: 10.1080/19475705.2023.2281241
Sergio Muñoz, Carlos Á. Iglesias • Big Data and Cognitive Computing
(2024)
The proliferation of fake news threatens the integrity of information ecosystems, creating a pressing need for effective and interpretable detection mechanisms. Recent advances in machine learning, particularly with transformer-based models...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bdcc8100129
Upendra Kumar Pradhan, Nitesh Kumar Sharma, Prakash Kumar, Ashwani Kumar et al. • PLoS ONE
(2021)
Formation of mature miRNAs and their expression is a highly controlled process. It is very much dependent upon the post-transcriptional regulatory events. Recent findings suggest that several RNA binding proteins beyond Drosha/Dicer are inv...
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Open Access (DOAJ)
DOI: 10.1371/journal.pone.0258550
Felix Brockherde, Leslie Vogt-Maranto, Li Li, Mark E. Tuckerman et al. • Nature Communications
(2017)
Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields. Machine learning holds the promise of learning the energy fun...
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DOI: https://doi.org/10.1038/s41467-017-00839-3
PMC: 5636838
Raymund C. Sison, Masamichi Shimura (1998)
After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge neces...
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Open Access
Qingyang Ling • Applied and Computational Engineering
(2023)
Machine learning is a field of study where the computer can learn for itself without a human explicitly hardcoding the knowledge for it. These algorithms make up the backbone of machine learning. This paper aims to study the field of machin...
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DOI: https://doi.org/10.54254/2755-2721/4/20230355
S. Vijayan, Chiranji Lal Chowdhary • Scientific Reports
(2025)
Abstract The agricultural industry significantly relies on autonomous systems for detecting and analyzing rice diseases to minimize financial and resource losses, reduce yield reductions, improve processing efficiency, and ensure healthy cr...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-92646-w
Alexandre Tkatchenko • Nature Communications
(2020)
Discovering chemicals with desired attributes is a long and painstaking process. Curated datasets containing reliable quantum-mechanical properties for millions of molecules are becoming increasingly available. The development of novel mach...
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DOI: https://doi.org/10.1038/s41467-020-17844-8
PMC: 7431574
Simon Willcock, Javier Martínez‐López, Danny A. P. Hooftman, Kenneth J. Bagstad et al. • Ecosystem Services
(2018)
Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within i...
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DOI: https://doi.org/10.1016/j.ecoser.2018.04.004
Khaled Bensid, Abdelhai Lati, Azeddine Benlamoudi, Brahim Elkhalil Ghouar et al. • Diagnostyka
(2022)
The spread of the coronavirus has claimed the lives of millions around the world, which led to the emergence of an economic and health crisis at the global level, which prompted many researchers to submit proposals for early diagnosis of th...
DOAJ
Open Access (DOAJ)
DOI: 10.29354/diag/156751
Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing
(2018)
Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs10071119
Ady Suwardi, Fuke Wang, Kun Xue, Ming‐Yong Han et al. • Advanced Materials
(2021)
Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to achieve desired biological responses. While there is constant evolution and innovation in materials with time, biomaterials research has been ham...
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DOI: https://doi.org/10.1002/adma.202102703
Marco Fiorucci, Marina Khoroshiltseva, Massimiliano Pontil, Arianna Traviglia et al. • Pattern Recognition Letters
(2020)
The application of Machine Learning (ML) to Cultural Heritage (CH) has evolved since basic statistical approaches such as Linear Regression to complex Deep Learning models. The question remains how much of this actively improves on the unde...
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DOI: https://doi.org/10.1016/j.patrec.2020.02.017