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A review of machine learning in scheduling

Haldun Aytuğ, Siddhartha Bhattacharyya, G.J. Koehler, Jane L. Snowdon • IEEE Transactions on Engineering Management (1994)

This paper has two primary purposes: to motivate the need for machine learning in scheduling systems and to survey work on machine learning in scheduling. In order to motivate the need for machine learning in scheduling, we briefly motivate...

OPENALEX DOI: https://doi.org/10.1109/17.293383

Machine Learning in Orthopedics: A Literature Review

Federico Cabitza, Angela Locoro, Giuseppe Banfi • Frontiers in Bioengineering and Biotechnology (2018)

In this paper we present the findings of a systematic literature review covering the articles published in the last two decades in which the authors described the application of a machine learning technique and method to an orthopedic probl...

OPENALEX cc-by DOI: https://doi.org/10.3389/fbioe.2018.00075 PMC: 6030383

Machine Learning in Healthcare Communication

Sarkar Siddique, James C. L. Chow • Encyclopedia (2021)

Machine learning (ML) is a study of computer algorithms for automation through experience. ML is a subset of artificial intelligence (AI) that develops computer systems, which are able to perform tasks generally having need of human intelli...

OPENALEX cc-by DOI: https://doi.org/10.3390/encyclopedia1010021

MARKETING ACTIVITIES OF IT COMPANIES: INFORMATION AND ORGANISATIONAL CAPABILITIES FOR DIGITAL PRODUCT DEVELOPMENT

Kostiantyn Fuks • Green, Blue and Digital Economy Journal (2024)

The purpose of this article is to provide a comprehensive examination of the informational and organisational capabilities of marketing activities in the market for digital products and services. It highlights the importance of data analysi...

DOAJ Open Access (DOAJ) DOI: 10.30525/2661-5169/2024-1-4

Real time identification of phishing attacks through machine learning enhanced browser extensions

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...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-35655-7

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

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...

DOAJ Open Access (DOAJ) DOI: 10.1038/s42003-021-02891-8

A review of the application of machine learning in water quality evaluation

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...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.eehl.2022.06.001 PMC: 10702893

Machine learning for ecosystem services

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...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.ecoser.2018.04.004

Efficient covid19 disease diagnosis based on cough signal processing and supervised machine learning

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...

DOAJ Open Access (DOAJ) DOI: 10.29354/diag/156751

Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction

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

Quantum algorithms for matrix geometric means

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...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41534-025-00973-7

RDDA: Rectified Discriminatory Delta-Adjust

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

Machine Learning‐Driven Biomaterials Evolution

Ady Suwardi, Fuke Wang, Kun Xue, Ming‐Yong Han et al. • Advanced Materials (2021)

Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to achieve desired biological responses. While there is constant evolution and innovation in materials with time, biomaterials research has been ham...

OPENALEX DOI: https://doi.org/10.1002/adma.202102703

Can machine learning be secure?

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...

OPENALEX DOI: https://doi.org/10.1145/1128817.1128824