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Showing 20 of 748 academic articles

An Instructional Optimization Method Based on Bidirectional Transformer and Reinforcement Learning

Ran Zhang, Xiaoping Wu, Xude Zhang, Li Xu • IEEE Access (2025)

With the rapid development of information technology, personalized education has become a key direction for improving the quality of online learning and optimizing individualized learning paths. However, accurately recommending appropriate ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3576878

Leveraging the Potential of Novel Data in Power Line Communication of Electricity Grids

Christoph Balada, Max Bondorf, Sheraz Ahmed, Markus Zdrallek et al. • IEEE Access (2025)

Electricity grids have become an essential part of daily life, even if they are often not noticed in everyday life. We usually only become particularly aware of this dependence by the time the electricity grid is no longer available. Howeve...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3560811

A satellite-derived, ground-measurement-independent monthly PM2.5 mass concentration dataset over China during 2000 - 2015

Ying Zhang, Zhengqiang Li, Yuanyuan Wei, Zongren Peng • Big Earth Data (2021)

Following the accelerated development of urbanization and industrialization, atmospheric particulate matter has become a significant threat to public health globally. Environmental health studies usually use the mass concentration of fine p...

DOAJ Open Access (DOAJ) DOI: 10.1080/20964471.2021.1918908

<bold>CroSSHeteroFL</bold>: Cross-Stratified Sampling Composition-Fitting to Federated Learning for Heterogeneous Clients

Vo Phuc Tinh, Hoang Hai Son, Nguyen Hoang Nam, Duc Ngoc Minh Dang et al. • IEEE Access (2024)

In the large-scale deployment of federated learning (FL) systems, the heterogeneity of clients, such as mobile phones and Internet of Things (IoT) devices with different configurations, constitutes a significant problem regarding fairness, ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3475737

AI-Driven Integration of Deep Learning With Lung Imaging, Functional Analysis, and Blood Gas Metrics for Perioperative Hypoxemia Prediction

Kecheng Huang, Chujun Wu, Rongpeng Pi, Jieyu Fang • JMIR Medical Informatics (2025)

This viewpoint article explores the transformative role of artificial intelligence (AI) in predicting perioperative hypoxemia through the integration of deep learning with multimodal clinical data, including lung imaging, pulmonary function...

DOAJ Open Access (DOAJ) DOI: 10.2196/73995

Personalized ideological content recommendation via reinforcement learning as a digital therapeutic for anxiety reduction in youth

Yu Wang • Discover Artificial Intelligence (2026)

Abstract Adaptive digital therapies are needed with increasing rates of youth anxiety. However, existing systems lack personalization and dynamic learning. To solve this, the proposed research is to build a personalized ideological content ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-01840-w

Explainable and perturbation-resilient model for cyber-threat detection in industrial control systems Networks

Urslla Uchechi Izuazu, Cosmas Ifeanyi Nwakanma, Dong-Seong Kim, Jae Min Lee • Discover Internet of Things (2025)

Abstract Deep learning-based intrusion detection systems (DL-IDS) have proven effective in detecting cyber threats. However, their vulnerability to adversarial attacks and environmental noise, particularly in industrial settings, limits pra...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43926-025-00100-0

Computer vision and AI-based cell phone usage detection in restricted zones of manufacturing industries

Uttam U. Deshpande, Supriya Shanbhag, Ramesh Koti, Ameet Chate et al. • Frontiers in Computer Science (2025)

Phone calls are strictly forbidden in certain locations due to the potential security threats. Mobile phones’ growing capabilities have also increased the risk of their misuse in places that are restricted, like manufacturing plants. Unauth...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcomp.2025.1535775

The Impact of Artificial Intelligence on Innovation

Iain Cockburn, Rebecca M. Henderson, Scott Stern • National Bureau of Economic Research (2018)

Artificial intelligence may greatly increase the efficiency of the existing economy.But it may have an even larger impact by serving as a new general-purpose "method of invention" that can reshape the nature of the innovation process and th...

OPENALEX public-domain DOI: https://doi.org/10.3386/w24449

Cobdock: an accurate and practical machine learning-based consensus blind docking method

Sadettin Y. Ugurlu, David McDonald, Huangshu Lei, Alan M. Jones et al. • Journal of Cheminformatics (2024)

Abstract Probing the surface of proteins to predict the binding site and binding affinity for a given small molecule is a critical but challenging task in drug discovery. Blind docking addresses this issue by performing docking on binding r...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13321-023-00793-x

Raman Spectroscopy Pre-Trained Encoder: A Self-Supervised Learning Approach for Data-Efficient Domain-Independent Spectroscopy Analysis

Abhiraam Eranti, Yogesh Tewari, Rafael Palacios, Amar Gupta • IEEE Access (2026)

Deep-learning methods have boosted the analytical power of Raman spectroscopy, yet they still require large, task-specific, labeled datasets and often fail to transfer across application domains. The study explores pre-trained encoders as a...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2026.3672109

Tachyon: Enhancing stacked models using Bayesian optimization for intrusion detection using different sampling approaches

T. Anitha Kumari, Sanket Mishra • Egyptian Informatics Journal (2024)

The integration of sensors in the monitoring of essential bodily measurements, air quality, and energy consumption in buildings demonstrates the importance of the Internet of Things (IoT) in everyday life. These security breaches are caused...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.eij.2024.100520

Convergence of Artificial Intelligence and Wearables in Strength Training and Performance Monitoring: A Scoping Review

Eleftherios Fyntikakis, Spyridon Plakias, Themistoklis Tsatalas, Minas A. Mina et al. • Applied Sciences (2026)

Background: Strength training (ST) is essential for enhancing athletic performance and reducing injury risk, yet traditional monitoring relies heavily on subjective assessment, limiting objective and individualized evaluation. Objective: Th...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16073565

Enhancing Online Security: A Novel Machine Learning Framework for Robust Detection of Known and Unknown Malicious URLs

Shiyun Li, Omar Dib • Journal of Theoretical and Applied Electronic Commerce Research (2024)

The rapid expansion of the internet has led to a corresponding surge in malicious online activities, posing significant threats to users and organizations. Cybercriminals exploit malicious uniform resource locators (URLs) to disseminate har...

DOAJ Open Access (DOAJ) DOI: 10.3390/jtaer19040141

ID-Det: Insulator Burst Defect Detection from UAV Inspection Imagery of Power Transmission Facilities

Shangzhe Sun, Chi Chen, Bisheng Yang, Zhengfei Yan et al. • Drones (2024)

The global rise in electricity demand necessitates extensive transmission infrastructure, where insulators play a critical role in ensuring the safe operation of power transmission systems. However, insulators are susceptible to burst defec...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones8070299

Silhouette-driven contrastive learning with hierarchical neighborhood structure for unsupervised clothes change person re-identification

Mingkun Li, Peng Xu • CAAI Artificial Intelligence Research (2026)

This paper addresses a highly challenging yet critical task: unsupervised person re-identification (Re-ID) under clothing changes. Unfortunately, existing unsupervised person Re-ID methods are mainly designed for short-term scenarios that r...

DOAJ Open Access (DOAJ) DOI: 10.26599/AIR.2025.9150050

Is cardiovascular risk profiling from UK Biobank retinal images using explicit deep learning estimates of traditional risk factors equivalent to actual risk measurements? A prospective cohort study design

Kohji Nishida, Ryo Kawasaki, Yiming Qian, Liangzhi Li et al. • BMJ Open (2024)

Objective Despite extensive exploration of potential biomarkers of cardiovascular diseases (CVDs) derived from retinal images, it remains unclear how retinal images contribute to CVD risk profiling and how the results can inform lifestyle m...

DOAJ Open Access (DOAJ) DOI: 10.1136/bmjopen-2023-078609