Reset
Showing 20 of 113 academic articles

Data-driven performance prediction of polymer solar cells using multi-layer perceptron with Bayesian hyperparameter tuning

Sun Ping • Materials Research Express (2026)

Polymer solar cells (PSCs) rely on labor-intensive trial-and-error experiments to optimize power conversion efficiency (PCE), due to complex coupling of molecular electronic properties, blend morphology and fabrication parameters. This work...

DOAJ Open Access (DOAJ) DOI: 10.1088/2053-1591/aeaacc

Machine learning insight in quality control and maintenance management of drilling mud pumps

Xiaoming Wu, Jingxuan Chang, Chengcheng Long, Hamzeh Ghorbani • Journal of Big Data (2026)

Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....

DOAJ Open Access (DOAJ) DOI: 10.1186/s40537-026-01475-9

Unraveling the relationship between key aroma components and sensory properties of fragrant peanut oils based on flavoromics and machine learning

Binfang Hu, Chunhua Zhang, Baijun Chu, Peishan Gu et al. • Food Chemistry: X (2023)

Key aroma components of 33 fragrant peanut oils with different aroma types were screened by combined using flavoromics and machine learning. A total of 108 volatile compounds were identified and 100 kinds of them were accurately quantified,...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.fochx.2023.100880

A cascaded classification approach using transfer learning and feature engineering for improved breast cancer classification

Chokri Ferkous, Ouissal Fadel, Abderrahmane Kefali, Hayet-Farida Merouani • IJAIN (International Journal of Advances in Intelligent Informatics) (2026)

The primary objective of this study is to design a cascaded classification framework that integrates deep-learning representations with handcrafted and clinical features to enhance the reliability and accuracy of breast cancer detection in ...

DOAJ Open Access (DOAJ) DOI: 10.26555/ijain.v12i1.1670

Performance Analysis and Optimization of Terahertz Metamaterial Absorbers Using Machine Learning-Based Inverse Modeling

Oishi Jyoti, Md. Samiul Habib, Nguyen Hoang Hai, S. M. Abdur Razzak • IEEE Access (2025)

We present a tunable broadband terahertz (THz) metamaterial absorber with a structurally simple, single-layered vanadium dioxide (VO2) elliptical ring resonator. This design achieves a wide, near-perfect absorption band (3.5–5 THz) w...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3631711

Development and validation of a predictive model for diabetic peripheral neuropathy with type 2 diabetes mellitus in Xinjiang, China

Asiguli Adili, Maihesumu Aikemu, Karanvir Singh Rana, Yihan Wei et al. • Scientific Reports (2025)

Abstract This study aims to identify risk factors associated with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetesmellitus (T2DM) and to develop a predictive model to support clinical decision-making. A total of 1,001 p...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-19922-7

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

Exploiting the features of deep residual network with SVM classifier for human posture recognition.

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...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0314959

Very Deep Convolutional Neural Networks for Complex Land Cover Mapping Using Multispectral Remote Sensing Imagery

Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing (2018)

Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs10071119

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

Deciphering Exhaled Aerosol Fingerprints for Early Diagnosis and Personalized Therapeutics of Obstructive Respiratory Diseases in Small Airways

Xiuhua April Si, Jinxiang Xi • Journal of Nanotheranostics (2021)

Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challengin...

DOAJ Open Access (DOAJ) DOI: 10.3390/jnt2030007

Exploring Traffic Patterns Through Network Programmability: Introducing SDNFLow, a Comprehensive OpenFlow-Based Statistics Dataset for Attack Detection

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-...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3378271

Cybersecurity in Smart Grids: Detecting False Data Injection Attacks Utilizing Supervised Machine Learning Techniques

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...

DOAJ Open Access (DOAJ) DOI: 10.3390/en17235870

Face mask mandates alter major determinants of adherence to protective health behaviours in Australia

Matthew Ryan, Jinjing Ye, Justin Sexton, Roslyn I. Hickson et al. • Royal Society Open Science (2025)

Face mask wearing is a protective health behaviour that helps mitigate the spread of infectious diseases such as influenza and COVID-19. Understanding predictors of face mask wearing can help refine public health messaging and policy in fut...

DOAJ Open Access (DOAJ) DOI: 10.1098/rsos.241941

Theoretical Potential of Green Hydrogen Production in Southern Morocco: Multi-Horizon Forecasting Using Machine Learning

Ikram Jennane, Yousef Farhaoui, Mohamed Khalifa Boutahir • Energies (2026)

This study investigates multi-horizon forecasting of solar-based green hydrogen (H2) production in Southern Morocco (Dakhla: 23.7° N, 15.9° W; Laâyoune: 27.2° N, 13.2° W; and Guelmim: 29.0° N, 10.1° W) using daily meteorological time series...

DOAJ Open Access (DOAJ) DOI: 10.3390/en19173984

Benchmarking Assessment of Supervised Machine Learning Algorithms of K-Nearest Neighbor, Random Forest, Decision Tree and Its Variants Based On Efficiency and Performance Metrics

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...

DOAJ Open Access (DOAJ)

Burnout Risk Profiles in Psychology Students: An Exploratory Study with Machine Learning

M. Graça Pereira, Martim Santos, Renata Magalhães, Cláudia Rodrigues et al. • Behavioral Sciences (2025)

University students are at increased risk of developing burnout and psychological distress from high academic workloads and performance expectations. The purpose of this study is to analyze the relationship between psychological and lifesty...

DOAJ Open Access (DOAJ) DOI: 10.3390/bs15040505

Using machine learning to predict persecutory beliefs based on aetiological models of delusions identified in a systematic literature search

Saskia Denecke, Felix Strakeljahn, Antonia Bott, Tania M. Lincoln • Communications Psychology (2025)

Abstract Aetiological models of delusions propose a broad range of predictors. The extent to which these predictors explain variance in persecutory beliefs across the continuum requires systematic investigation. As part of a previous review...

DOAJ Open Access (DOAJ) DOI: 10.1038/s44271-025-00311-9

Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment

Shourong Lu, Ying Yang, Qiao Xu, Shuqiang Wang et al. • Frontiers in Neurology (2022)

Gut microbial alteration is closely associated with brain disorders including cognitive impairment (CI). Gut microbes have the potential to predicate the development of diseases. However, the gut microbial markers for CI remain to be elucid...

DOAJ Open Access (DOAJ) DOI: 10.3389/fneur.2022.834403