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Academic Articles & Research Papers
Showing 20 of 987 academic articles
Ammar Alnmr, Ammar Alnmr, Rashad Alsirawan, Haidar Hosamo et al. • Frontiers in Built Environment
(2026)
Efficient and reliable design of Geosynthetic Reinforced Pile-Supported (GRPS) embankments on soft ground remains challenging due to the complex nonlinear soil–structure interaction and the high computational cost of repeated numerical anal...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fbuil.2026.1829950
Marcos Gabriel Mendes Lauande, Geraldo Braz Júnior, João Dallyson Sousa de Almeida, Vandecia Rejane Monteiro Fernandes et al. • Data in Brief
(2025)
Penile cancer has an incidence strongly linked to sociocultural factors, being more common in underdeveloped countries like Brazil, where it represents approximately 2% of cancers affecting men. This dataset was created to address the scarc...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.dib.2025.111823
Ployrada Suvarnakuta, Intouch Prakaisak, Pittipol Kantavat, Boonserm Kijsirikul et al. • Engineered Science
(2025)
This study proposes a machine learning framework for predicting perceived urban quality of life (QoL) by integrating visual features from street-level imagery with personal attributes, including demographic, socioeconomic, and travel behavi...
DOAJ
Open Access (DOAJ)
DOI: 10.30919/es1972
Mafalda Reis Pereira, Mafalda Reis Pereira, Filipe Neves dos Santos, Fernando Tavares et al. • Frontiers in Plant Science
(2023)
Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant dis...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fpls.2023.1242201
Ahmed Medhat Zayed, Arne Janssens, Pavlos Mamouris, Nicolas Delvaux • BMC Medical Informatics and Decision Making
(2024)
Abstract Background The integrity of clinical research and machine learning models in healthcare heavily relies on the quality of underlying clinical laboratory data. However, the preprocessing of this data to ensure its reliability and acc...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12911-024-02652-7
G. Baaklini, G. Baaklini, R. El Hourany, M. Fakhri et al. • Ocean Science
(2022)
The eastern Mediterranean surface circulation is highly energetic and composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping t...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/os-18-1491-2022
Juan Carlos Ramírez-Vázquez, Guadalupe Esmeralda Rivera-García, Marco Antonio Gómez-Guzmán, Marco Antonio Díaz-Martínez et al. • Technologies
(2026)
A substantial number of students with hearing impairments are enrolled in higher education, motivating the development of inclusive assistive technologies that reduce communication barriers. This study developed and evaluated a prototype el...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/technologies14030189
Meenakshi Sudarvizhi Seenipeyathevar, Prasath Palaniappan, Vijayakumar Arumugam, Vivek Sivakumar et al. • Engineering Reports
(2026)
ABSTRACT This study deals with an integrated experimental‐machine learning framework for wear estimation in functionally graded composites made from recycled magnesium machining chips, using low‐cost ceramic fibers as reinforcement with the...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/eng2.70686
John R. Kitchin • Nature Catalysis
(2018)
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DOI: https://doi.org/10.1038/s41929-018-0056-y
Kevin P. Murphy (2012)
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict fu...
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Jing Wei, Xuan Chu, Xiangyu Sun, Kun Xu et al. • InfoMat
(2019)
Abstract Traditional methods of discovering new materials, such as the empirical trial and error method and the density functional theory (DFT)‐based method, are unable to keep pace with the development of materials science today due to the...
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cc-by
DOI: https://doi.org/10.1002/inf2.12028
Πάνος Λουρίδας, Christof Ebert • IEEE Software
(2016)
In machine learning, a computer first learns to perform a task by studying a training set of examples. The computer then performs the same task with data it hasn't encountered before. This article presents a brief overview of machine-learni...
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DOI: https://doi.org/10.1109/ms.2016.114
Pat Langley B (1995)
Elements of Machine Learning by Pat Langley Preface 1. An overview of machine learning 1.1 The science of machine learning 1.2 Nature of the environment 1.3 Nature of representation and performance 1.4 Nature of the learning component 1.5 F...
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Juan Carrasquilla, Roger G. Melko • Nature Physics
(2017)
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Open Access
DOI: https://doi.org/10.1038/nphys4035
Giuseppe Carleo, J. I. Cirac, Kyle Stuart Cranmer, Laurent Daudet et al. • Reviews of Modern Physics
(2019)
In October 2018 an APS Physics Next Workshop on Machine Learning was held in Riverhead, NY. This article reviews and summarizes the proceedings of this very broad, emerging field.This needs to be a placard in the left-hand column, with a cu...
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Open Access
DOI: https://doi.org/10.1103/revmodphys.91.045002
Radford M. Neal • Technometrics
(2007)
(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366....
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DOI: https://doi.org/10.1198/tech.2007.s518
JUDE W. SHAVLIK, Thomas E. Deitterich, Thomas G. Dietterich (1991)
From the Publisher:
The ability to learn is a fundamental characteristic of intelligent behavior. Consequently, machine learning has been a focus of artificial intelligence since the beginnings of AI in the 1950s. The 1980s saw tremendous ...
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Bernhard Schölkopf • ACM eBooks
(2022)
Graphical causal inference as pioneered by Judea Pearl arose from research on artificial intelligence (AI), and for a long time had little connection to the field of machine learning. This article discusses where links have been and should ...
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Open Access
DOI: https://doi.org/10.1145/3501714.3501755
Peter de B. Harrington (2012)
SummaryMachine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to bui...
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Solveig Badillo, Balázs Bánfai, Fabian Birzele, Iakov I. Davydov et al. • Clinical Pharmacology & Therapeutics
(2020)
In the last few years, machine learning (ML) and artificial intelligence have seen a new wave of publicity fueled by the huge and ever-increasing amount of data and computational power as well as the discovery of improved learning algorithm...
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cc-by-nc-nd
DOI: https://doi.org/10.1002/cpt.1796
PMC: 7189875