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Academic Articles & Research Papers
Showing 20 of 1,254 academic articles
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
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
Iason Batzianoulis, Fumiaki Iwane, Shupeng Wei, Carolina Gaspar Pinto Ramos Correia et al. • Communications Biology
(2021)
Teaching an assistive robotic manipulator to move objects in a cluttered table requires demonstrations from expert operators, but what if the experts are individuals with motor disabilities? Batzianoulis et al. propose a learning approach w...
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Open Access (DOAJ)
DOI: 10.1038/s42003-021-02891-8
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
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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DOI: https://doi.org/10.1016/j.eehl.2022.06.001
PMC: 10702893
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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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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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
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
Qinxia HAO, Haitao SHANG • Meikuang Anquan
(2023)
In order to accurately predict the risk level of coal mine gas explosion accidents, based on the feature vector in line with the actual situation, the particle swarm optimization probabilistic neural network (RWPSO-PNN) is improved to reali...
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Open Access (DOAJ)
DOI: 10.13347/j.cnki.mkaq.2023.10.034
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
Nana Liu, Qisheng Wang, Mark M. Wilde, Zhicheng Zhang • npj Quantum Information
(2025)
Abstract Matrix geometric means between two positive definite matrices can be defined from distinct perspectives—as solutions to certain nonlinear systems of equations, as points along geodesics in Riemannian geometry, and as solutions to c...
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Open Access (DOAJ)
DOI: 10.1038/s41534-025-00973-7
Het Patel, Aditya Kansara, Boppuru Rudra Prathap, Kukatlapalli Pradeep Kumar • Measurement: Sensors
(2023)
The exponential rise in the use of social media has resulted in a massive increase in the volume of unstructured text created. This content is presented through messages, conversations, postings, and blogs. Microblogging has become a popula...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.measen.2023.100768
Alexander I. Kochegurov, Vladislav I. Denisov, Elizaveta A. Zadorozhnykh • Известия Томского политехнического университета: Инжиниринг георесурсов
(2024)
Relevance. Core studies in the oil and gas industry allow us to obtain some filtration and capacity characteristics of rocks, as well as to give an idea of the composition and structure of the subsoil. This information is extremely importan...
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Open Access (DOAJ)
DOI: 10.18799/24131830/2024/9/4792
Shobhit K. Patel, Juveriya Parmar, Vijay Katkar, Fahad Ahmed Al-Zahrani et al. • Alexandria Engineering Journal
(2022)
The solar spectrum energy absorption is very important for designing any solar absorber. The need for absorbing visible, infrared, and ultraviolet regions is increasing as most of the absorbers absorb visible regions. We propose a metasurfa...
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Open Access (DOAJ)
DOI: 10.1016/j.aej.2022.03.080
Ziad F. Doughan, Sari S. Itani • IEEE Access
(2025)
This paper introduces Rectified Discriminatory Delta-Adjust (RDDA), a novel methodology that enhances interpolation-based predictive modeling through adaptive sensitivity parameters. Building upon the foundational Delta-Adjust algorithm, RD...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3641537
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
Marco Barreno, Blaine A. Nelson, Russell Sears, Anthony D. Joseph et al. • ACM Asia Conference on Computer and Communications Security (ASIA CCS)
(2006)
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. However, machine learning algorithms themselves can be a targe...
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DOI: https://doi.org/10.1145/1128817.1128824
Sheena Angra, Sachin Ahuja • International Conference on Big Data Analytics and Computational Intelligence (ICBDAC)
(2017)
Nowadays, large amount of data is available everywhere. Therefore, it is very important to analyze this data in order to extract some useful information and to develop an algorithm based on this analysis. This can be achieved through data m...
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DOI: https://doi.org/10.1109/icbdaci.2017.8070809