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Academic Articles & Research Papers
Showing 20 of 757 academic articles
Saleh Albahli • Future Internet
(2019)
Since the introduction of just-in-time effort aware defect prediction, many researchers are focusing on evaluating the different learning methods, which can predict the defect inducing changes in a software product. In order to predict thes...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/fi11120246
Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu • Journal of Computational Chemistry
(2017)
The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning,...
OPENALEX
Open Access
DOI: https://doi.org/10.1002/jcc.24764
Anna Teresa Seiche, Lucas Wittstruck, Thomas Jarmer • Sensors
(2024)
In order to meet the increasing demand for crops under challenging climate conditions, efficient and sustainable cultivation strategies are becoming essential in agriculture. Targeted herbicide use reduces environmental pollution and effect...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s24051544
S. Mostafa Mousavi, Gregory C. Beroza • Science
(2022)
Seismic waves from earthquakes and other sources are used to infer the structure and properties of Earth's interior. The availability of large-scale seismic datasets and the suitability of deep-learning techniques for seismic data processin...
OPENALEX
DOI: https://doi.org/10.1126/science.abm4470
Jakob Mannstadt, Arash Rahimi‐Iman • Advanced Sensor Research
(2025)
Abstract A machine‐learning (ML) non‐contact method to determine the temperature of a laser gain medium via its laser emission with a trained few‐layer neural‐network (NN) model is presented. The training of the feed‐forward NN enables the ...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/adsr.70009
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
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
Pengfei Li, Yue Jia • Sensors
(2026)
Diameter at breast height (DBH) is a fundamental structural parameter for forest inventory and ecological analysis. However, field-based measurements (e.g., diameter tape surveys) are labor-intensive and inefficient for large-scale applicat...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s26092873
Albert P. Bartók, Sandip De, Carl R. Poelking, Noam Bernstein et al. • Science Advances
(2017)
Determining the stability of molecules and condensed phases is the cornerstone of atomistic modeling, underpinning our understanding of chemical and materials properties and transformations. We show that a machine-learning model, based on a...
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cc-by-nc
DOI: https://doi.org/10.1126/sciadv.1701816
PMC: 5729016
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...
OPENALEX
cc-by
DOI: https://doi.org/10.1038/s41467-020-17844-8
PMC: 7431574
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...
OPENALEX
DOI: https://doi.org/10.1002/adma.202102703
Matthias Seeger • International Journal of Neural Systems
(2004)
Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many dee...
OPENALEX
Open Access
DOI: https://doi.org/10.1142/s0129065704001899
Philomena Schlexer, Kirsten T. Winther, José Antonio Garrido Torres, Verena Streibel et al. • ChemCatChem
(2019)
Abstract Big data and artificial intelligence has revolutionized science in almost every field – from economics to physics. In the area of materials science and computational heterogeneous catalysis, this revolution has led to the developme...
OPENALEX
DOI: https://doi.org/10.1002/cctc.201900595
Mazen Kadhim Shekedl, Farhad Salimi, Neda Azimi • Journal of Renewable Energy and Environment
(2026)
The efficiency of bio-oil production from municipal solid waste was investigated using microwave-assisted pyrolysis. The effects of temperature, pyrolysis time, and microwave power on bio-oil yield were evaluated using Response Surface Meth...
DOAJ
Open Access (DOAJ)
DOI: 10.30501/jree.2026.563599.2716
Oscar Lahuerta, Claudio Carretero, Luis Angel Barragan, Denis Navarro et al. • IEEE Open Journal of the Industrial Electronics Society
(2026)
This article introduces a hybrid variant of a physics-informed neural network (PINN) that is designed to effectively capture both the rapid dynamics of electrical variables and the slower dynamics of state parameters in a domestic induction...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/OJIES.2026.3663897
Sagar Chokshi, Piyush Gohil, Vijay Parmar, Vijaykumar Chaudhary • Mechanics of Advanced Composite Structures
(2025)
Machine Learning has become prevalent nowadays for predicting data on the mechanical properties of various materials and is widely used in various polymeric applications. In the present study, Artificial Neural Network (ANN), a computationa...
DOAJ
Open Access (DOAJ)
DOI: 10.22075/macs.2024.33874.1664
Jörn Lötsch, Alfred Ultsch • Pain
(2017)
1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...
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cc-by-nc-nd
DOI: https://doi.org/10.1097/j.pain.0000000000001118
PMC: 5895117
Ming Han, Ge Sun, Paul F. Nealey, Juan J. de Pablo • npj Computational Materials
(2025)
Abstract Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41524-025-01836-7
Chao Xu, Dezhi Chen, Xiaofu Zhang, Qi Wang et al. • Nature Communications
(2026)
Abstract High temperature Nb-Si based alloys face a critical challenge: achieving adequate room-temperature fracture toughness ( > 18 MPa·m1/2) for processing while maintaining high-temperature strength, properties that typically compete wi...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41467-026-75353-6