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Academic Articles & Research Papers
Showing 20 of 3,783 academic articles
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
Irfan Kareem, Syed Farooq Ali, Muhammad Bilal, Muhammad Shehzad Hanif • PLoS ONE
(2024)
Over the last decade, there have been a lot of advances in the area of human posture recognition. Among multiple approaches proposed to solve this problem, those based on deep learning have shown promising results. Taking another step in th...
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Open Access (DOAJ)
DOI: 10.1371/journal.pone.0314959
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
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
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
Subrata Chakraborty, Biswajeet Pradhan • Sensors
(2024)
Machine learning (ML) models have experienced remarkable growth in their application for multimodal data analysis over the past decade [...]...
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Open Access (DOAJ)
DOI: 10.3390/s24092874
Jie Zhang, Zipeng Wang, Jinzheng Hu, Shihao Xiao et al. • Journal of Rock Mechanics and Geotechnical Engineering
(2022)
The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time (SFT). The observational and model uncertainties could lead the predicted SFT calculated from the phenomen...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrmge.2021.09.010
Alejandro Casallas, Camila Jiménez-Saenz, Victor Torres, Miguel Quirama-Aguilar et al. • Sensors
(2022)
Throughout the years, wildfires have negatively impacted ecological systems and urban areas. Hence, reinforcing territorial risk management strategies against wildfires is essential. In this study, we built an early alert system (EAS) with ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s22228790
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
Van-Ngoc Pham, Huu-Dao Do, Thi Phuong Khue Nguyen, Van-Khanh Tran et al. • Tạp chí Khoa học và Công nghệ
(2026)
This study develops a data-driven framework using Extreme Gradient Boosting (XGBoost) to predict the Indirect Tensile Strength (ITS) of cement-treated clayey soils. Using 180 specimens with five input variables - cement content, curing time...
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Open Access (DOAJ)
DOI: 10.31130/ud-jst.2026.24(7B).582E
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
Yun Liu, Po-Hsuan Cameron Chen, Jonathan Krause, Lily H. Peng • JAMA
(2019)
In recent years, many new clinical diagnostic tools have been developed using complicated machine learning methods. Irrespective of how a diagnostic tool is derived, it must be evaluated using a 3-step process of deriving, validating, and e...
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DOI: https://doi.org/10.1001/jama.2019.16489
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...
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Open Access
DOI: https://doi.org/10.1142/s0129065704001899
Haoxin Mai, Tu C. Le, Dehong Chen, David Alan Winkler et al. • Chemical Reviews
(2022)
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, and providing solutions to environmental pollution. Improved processes for catalyst design and a better unde...
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DOI: https://doi.org/10.1021/acs.chemrev.2c00061
Khader Shameer, Kipp W. Johnson, Benjamin Scott Glicksberg, Joel T. Dudley et al. • Heart
(2018)
Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from data, allowing computers to find hidden insights without being explicitly programmed where to look. These include a family of operations encomp...
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DOI: https://doi.org/10.1136/heartjnl-2017-311198