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Academic Articles & Research Papers
Showing 20 of 50 academic articles
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
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
Khaled Bensid, Abdelhai Lati, Azeddine Benlamoudi, Brahim Elkhalil Ghouar et al. • Diagnostyka
(2022)
The spread of the coronavirus has claimed the lives of millions around the world, which led to the emergence of an economic and health crisis at the global level, which prompted many researchers to submit proposals for early diagnosis of th...
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Open Access (DOAJ)
DOI: 10.29354/diag/156751
Jorge Buzzio-Garcia, Jaime Vergara, Santiago Rios-Guiral, Christian Garzon et al. • IEEE Access
(2024)
In the contemporary cybersecurity landscape, robust attack detection mechanisms are important for organizations. However, the current state of research in Software-Defined Networking (SDN) suffers from a notable lack of recent SDN-OpenFlow-...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3378271
Anwer Shees, Mohd Tariq, Arif I. Sarwat • Energies
(2024)
By integrating advanced technologies and data-driven systems in smart grids, there has been a significant revolution in the energy distribution sector, bringing a new era of efficiency and sustainability. Nevertheless, with this advancement...
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Open Access (DOAJ)
DOI: 10.3390/en17235870
Y. Y. Abdullahi, A. S. Nur, A. Sale • Journal of Applied Sciences and Environmental Management
(2025)
Machine learning provides more verbose algorithms capable of accurately predicting, classifying groups as needed. Consequently, the objective of this paper is to assess the benchmarking of Supervised Machine Learning Algorithms of K-Nearest...
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Open Access (DOAJ)
Jörn Lötsch, Alfred Ultsch • Pain
(2017)
1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...
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cc-by-nc-nd
DOI: https://doi.org/10.1097/j.pain.0000000000001118
PMC: 5895117
James L. Melville, Edmund K. Burke, Jonathan D. Hirst • Combinatorial Chemistry & High Throughput Screening
(2009)
In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a partic...
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DOI: https://doi.org/10.2174/138620709788167980
Marieth Agnes Guillen-García, Osnamir Elias Bru-Cordero, Cristian David Correa-Álvarez • Big Data and Cognitive Computing
(2026)
Student retention analytics often treats withdrawal as a single outcome, although students may attribute dropout intention to personal, socioeconomic, and academic pressures simultaneously. We benchmarked nine supervised classifiers for ide...
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Open Access (DOAJ)
DOI: 10.3390/bdcc10080274
Maher Abuhussain, Ali Hussain Alhamami, Khaled Almazam, Omar Humaidan et al. • Buildings
(2025)
This study introduces a comprehensive framework combining building information modeling (BIM), project management body of knowledge (PMBOK), and machine learning (ML) to optimize energy efficiency and reduce environmental impacts in Riyadh’...
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Open Access (DOAJ)
DOI: 10.3390/buildings15173031
K. W. DeGregory, Patrick K. Kuiper, Thomas DeSilvio, James D. Pleuss et al. • Obesity Reviews
(2018)
Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine lea...
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Open Access
DOI: https://doi.org/10.1111/obr.12667
PMC: 8176949
Arvind Kumar Tiwari • IGI Global eBooks
(2019)
Machine learning refers to the changes in systems that perform tasks associated with artificial intelligence. This chapter presents introduction types and application of machine learning. This chapter also presents the basic concepts relate...
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DOI: https://doi.org/10.4018/978-1-7998-0414-7.ch003
Tan Yan Lin, Pang Ying Han, Ooi Shih Yin, Khoh Wee How et al. • Journal of Engineering Technology and Applied Physics
(2023)
In the telecom industry, predicting customer churn is crucial for improving customer retention. In literature, the use of single classifiers is predominantly focused. Customer data is complex data due to class imbalance and contain multiple...
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Open Access (DOAJ)
DOI: 10.33093/jetap.2023.5.2.12
Cheng-Hong Yang, Chih-Hsien Wu, Kuei-Hau Luo, Huang-Chih Chang et al. • Ecotoxicology and Environmental Safety
(2024)
Air pollution has become a major global threat to human health. Urbanization and industrialization over the past few decades have increased the air pollution. Plausible connections have been made between air pollutants and dementia. This st...
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Open Access (DOAJ)
DOI: 10.1016/j.ecoenv.2024.116885
David John Lary, Amir H. Alavi, Amir H. Gandomi, Annette L. Walker • Geoscience Frontiers
(2015)
Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.gsf.2015.07.003
Oswald Campesato • De Gruyter eBooks
(2020)
This book is designed to provide the reader with basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fun...
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DOI: https://doi.org/10.1515/9781683924937
Jongho Lee, Jiuk Shin, Jaewook Lee, Chorong Park et al. • Applied Sciences
(2023)
Large fires in factories cause severe human casualties and property damage. Thus, preparing more economical and efficient management strategies for fire prevention can significantly improve fire safety. This study deals with property damage...
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Open Access (DOAJ)
DOI: 10.3390/app132111866
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
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...
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Open Access (DOAJ)
DOI: 10.3389/fbuil.2026.1829950