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Academic Articles & Research Papers
Showing 20 of 4,934 academic articles
Sun-Feel Yang, So-Won Choi, Eul-Bum Lee • Energies
(2023)
The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affe...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/en16114271
Heechan Han, Boran Kim, Kyunghun Kim, Donghyun Kim et al. • Water Science and Technology
(2023)
Precipitation is one of the driving forces in water cycles, and it is vital for understanding the water cycle, such as surface runoff, soil moisture, and evapotranspiration. However, missing precipitation data at the observatory becomes an ...
DOAJ
Open Access (DOAJ)
DOI: 10.2166/wst.2023.237
Biprateep Dey, David Zhao, Brett H Andrews, Jeffrey A Newman et al. • Machine Learning: Science and Technology
(2025)
Key science questions, such as galaxy distance estimation and weather forecasting, often require knowing the full predictive distribution of a target variable Y given complex inputs X . Despite recent advances in machine learning and physic...
DOAJ
Open Access (DOAJ)
DOI: 10.1088/2632-2153/ae1f05
Mario D. Molina, Filiz Garip • Annual Review of Sociology
(2019)
Machine learning is a field at the intersection of statistics and computer science that uses algorithms to extract information and knowledge from data. Its applications increasingly find their way into economics, political science, and soci...
OPENALEX
Open Access
DOI: https://doi.org/10.1146/annurev-soc-073117-041106
Steven L. Brunton, Bernd R. Noack, Petros Koumoutsakos • Annual Review of Fluid Mechanics
(2019)
The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning (ML) offers a wealth of techniq...
OPENALEX
Open Access
DOI: https://doi.org/10.1146/annurev-fluid-010719-060214
Thomas G. Dietterich • ACM Computing Surveys
(1995)
suggests a reasonable line of research: find algorithms that can search the hypothesis class better. Hence, there is been extensive research in applying second-order methods to fit neural networks and in conducting much more thorough search...
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Open Access
DOI: https://doi.org/10.1145/212094.212114
Tomasz Rokicki, Piotr Bórawski, Aneta Bełdycka-Bórawska, Bogdan Klepacki • Applied Sciences
(2026)
Port activity anomalies are rare but may signal operational constraints relevant to supply chains. The aim of the study was to develop and empirically evaluate a calibrated machine learning framework for forecasting rare, algorithmically de...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app16189017
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
Doyeon Weon, Kyungchun Lee • IEEE Access
(2020)
In this paper, we propose a novel learning-aided sphere decoding (SD) scheme for large multiple-input-multiple-output systems, namely, deep path prediction-based sphere decoding (DPP-SD). In this scheme, we employ a neural network (NN) to p...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.2987375
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
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...
OPENALEX
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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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...
OPENALEX
Open Access
DOI: https://doi.org/10.1103/revmodphys.91.045002
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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Bradley James Erickson, Panagiotis D. Korfiatis, Zeynettin Akkus, Timothy Lee Kline • Radiographics
(2017)
Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the ma...
OPENALEX
Open Access
DOI: https://doi.org/10.1148/rg.2017160130
PMC: 5375621
Elisabeth Källström, Tomas Olsson, John Lindström, Lars Hakansson et al. • International Journal of Prognostics and Health Management
(2018)
In order to reduce unnecessary stops and expensive downtime originating from clutch failure of construction equipment machines; adequate real time sensor data measured on the machine in combination with feature extraction and classification...
DOAJ
Open Access (DOAJ)
DOI: doi:10.36001/ijphm.2018.v9i1.2693