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Academic Articles & Research Papers
Showing 20 of 987 academic articles
Yajing Tian, Yuyang Wang, Shasha Yin, Jia Lu et al. • Energies
(2024)
U-tube steam generators (UTSGs) are crucial in nuclear power plants, serving as the interface between the primary and secondary coolant loops. UTSGs ensure efficient heat exchange, operational stability, and safety, directly impacting the p...
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Open Access (DOAJ)
DOI: 10.3390/en17163916
Chang Lai, Jiyao Xu, Zhishuang Lin, Kun Wu et al. • Space Weather
(2023)
Abstract For the first time, we used the machine learning method to analyze the statistical occurrence and propagation characteristics of nighttime medium‐scale traveling ionospheric disturbances (MSTIDs) from October 2011 to December 2021 ...
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Open Access (DOAJ)
DOI: 10.1029/2023SW003430
Claire Tardiveau, Claire Tardiveau, Guillaume Monneret, Guillaume Monneret et al. • Frontiers in Immunology
(2022)
Immune responses affiliated with COVID-19 severity have been characterized and associated with deleterious outcomes. These approaches were mainly based on research tools not usable in routine clinical practice at the bedside. We observed th...
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Open Access (DOAJ)
DOI: 10.3389/fimmu.2022.1022750
Monika Dandotiya, Nikhil Kumar Goyal, Ajay Khunteta, Babita Tiwari • Scientific Reports
(2026)
Abstract Phishing attack continues to rank among the deadliest online threats. They create phony websites in an attempt to obtain personal data. This study offers a framework for a browser extension that uses machine learning to examine URL...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-35655-7
Simran Saggu, Hirad Daneshvar, Reza Samavi, Paulo Pires et al. • BMC Medical Informatics and Decision Making
(2024)
Abstract Background The proportion of Canadian youth seeking mental health support from an emergency department (ED) has risen in recent years. As EDs typically address urgent mental health crises, revisiting an ED may represent unmet menta...
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Open Access (DOAJ)
DOI: 10.1186/s12911-024-02450-1
J. R. Quinlan (1992)
Classifier systems play a major role in machine learning and knowledge-based systems, and Ross Quinlan's work on ID3 and C4.5 is widely acknowledged to have made some of the most significant contributions to their development. This book is ...
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Hongyu Liu, Bo Lang • Applied Sciences
(2019)
Networks play important roles in modern life, and cyber security has become a vital research area. An intrusion detection system (IDS) which is an important cyber security technique, monitors the state of software and hardware running in th...
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DOI: https://doi.org/10.3390/app9204396
Mengyuan Zhu, Jiawei Wang, Xiao Yang, Yu Zhang et al. • Eco-Environment & Health
(2022)
With the rapid increase in the volume of data on the aquatic environment, machine learning has become an important tool for data analysis, classification, and prediction. Unlike traditional models used in water-related research, data-driven...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.eehl.2022.06.001
PMC: 10702893
Julia Westermayr, Philipp Marquetand • Chemical Reviews
(2020)
Electronically excited states of molecules are at the heart of photochemistry, photophysics, as well as photobiology and also play a role in material science. Their theoretical description requires highly accurate quantum chemical calculati...
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DOI: https://doi.org/10.1021/acs.chemrev.0c00749
PMC: 8391943
Vijay K. Vemuri • Journal of Information Technology Case and Application Research
(2020)
Advances in Artificial intelligence and machine learning have developed beyond the theoretical realm. In fact, several day-to-day applications are currently in use. Although artificial intelligence......
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DOI: https://doi.org/10.1080/15228053.2020.1766224
Yves Kodratoff • CERN Document Server (European Organization for Nuclear Research)
(1988)
1 Why Machine Learning and AI: The Contributions of AI to Learning Techniques 2 Theoretical Foundations for Machine Learning 3 Representation of Complex Knowledge by Clauses 4 Representation of Knowledge about Actions and the Addition of Ne...
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• Human-computer interaction series
(2018)
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DOI: https://doi.org/10.1007/978-3-319-90403-0
Ral Garreta, Guillermo Moncecchi • International Linear Collider
(2013)
The book adopts a tutorial-based approach to introduce the user to Scikit-learn.If you are a programmer who wants to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this...
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Kaiyang Qu, Fei Guo, Xiangrong Liu, Yuan Lin et al. • Frontiers in Microbiology
(2019)
Microorganisms are ubiquitous and closely related to people's daily lives. Since they were first discovered in the 19th century, researchers have shown great interest in microorganisms. People studied microorganisms through cultivation, but...
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DOI: https://doi.org/10.3389/fmicb.2019.00827
PMC: 6482238
Stephen Marsland (2009)
Traditional books on machine learning can be divided into two groups - those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is r...
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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
Luc De Raedt, Peter A. Flach • Lecture notes in computer science
(2001)
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DOI: https://doi.org/10.1007/3-540-44795-4
Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola • The Annals of Statistics
(2008)
We review machine learning methods employing positive definite kernels. These methods formulate learning and estimation problems in a reproducing kernel Hilbert space (RKHS) of functions defined on the data domain, expanded in terms of a ke...
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Open Access
DOI: https://doi.org/10.1214/009053607000000677
Min-Hwa Choi, Woongchang Yoon • IEEE Access
(2025)
Port congestion and prolonged ship waiting times pose challenges for global trade and increase operational costs and inefficiencies. In this study, a novel machine learning-based predictive approach was proposed to improve port operations b...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3566429