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Guarding against artificial intelligence – hallucinated citations: The case for full-text reference deposit.

Alex Glynn • European Science Editing (2025)

The tendency of generative artificial intelligence (AI) to ‘hallucinate’ false information is well known; AI-generated citations to non-existent sources have penetrated the bibliographies of peer-reviewed publications. D...

DOAJ Open Access (DOAJ) DOI: 10.3897/ese.2025.e153973

Investigations on Rockmass Structure Characteristics and Mechanical Mining Efficiency and Economics in the Jinchuan No. 3 Mine With Hard Rock

Jian Zhao, Dan Huang, Daming Zhu, Mingyue Wang et al. • Advances in Civil Engineering (2026)

Geomechanical characterization is crucial for assessing the feasibility of the mechanical construction method in geotechnical engineering, which is a construction method that neither uses explosives nor involves blasting operations. But for...

DOAJ Open Access (DOAJ) DOI: 10.1155/adce/2598677

AI-driven data fusion modeling for enhanced prediction of mixed-mode I/III fracture toughness

Anantaya Timtong, Atthaphon Ariyarit, Wanwanut Boongsood, Prasert Aengchuan et al. • Results in Engineering (2024)

This research evaluates the use of artificial intelligence to enhance the accuracy of predictions for mixed-mode I/III fracture toughness in polymethyl methacrylate . Traditionally, assessing fracture toughness relies heavily on destructive...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.rineng.2024.103289

The Effects of Large Language Models on the Generation of Multiple-choice Questions in Medical Education: A Scoping Review

Baleegh Elsir Ahmed Mohammed, Tanzeel Elsir Ahmed Mohammed, Anthony Paul Breitbach • Sudan Journal of Medical Sciences (2026)

Background: Constructing high-quality multiple-choice questions (MCQs) is critical yet resource-intensive in medical education. Large language models (LLMs), such as ChatGPT, have become promising tools for generating MCQs in medical educat...

DOAJ Open Access (DOAJ) DOI: 10.18502/sjms.v21i2.19868

Current Signature-Based Bearing Fault Severity Classification Using a Robust Multilevel Cascaded Framework

Korawege N. C. Jayasena, Battur Batkhishig, Babak Nahid-Mobarakeh, Ali Emadi • IEEE Access (2025)

Bearing faults are a critical concern in electrical machines, particularly permanent magnet synchronous motors (PMSMs), commonly used in electric vehicles. Early and accurate classification of bearing fault severity is essential for predict...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3589750

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

Developing Artificial Intelligence-Powered Monetary Policy Communication Indicators for Macroeconomic Inquiries in Ghana

Francis Mawuli Abude, Jones Odei-Mensah, Eric Schaling • Communicare (2024)

Central bank communication is a valuable source of information designed to shape the expectations of economic agents within and outside an economy. In particular, the content of Monetary Policy Committees’ press releases and statements refl...

DOAJ Open Access (DOAJ) DOI: 10.36615/jcsa.v43i1.2779

<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

Artificial intelligence, systemic risks, and sustainability

Victor Galaz, Miguel Ángel Centeno, Peter W. Callahan, Amar Causevic et al. • Technology in Society (2021)

Automated decision making and predictive analytics through artificial intelligence, in combination with rapid progress in technologies such as sensor technology and robotics are likely to change the way individuals, communities, governments...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.techsoc.2021.101741

IoT-Equipped and AI-Enabled Next Generation Smart Agriculture: A Critical Review, Current Challenges and Future Trends

Sameer Qazi, Bilal A. Khawaja, Qazi Umar Farooq • IEEE Access (2022)

Smart agriculture techniques have recently seen widespread interest by farmers. This is driven by several factors, which include the widespread availability of economically-priced, low-powered Internet of Things (IoT) based wireless sensors...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2022.3152544

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

Enhancing underwater target detection: Fusion of spatio‐temporal incompletely‐aligned AIS and sonar information via DTW and multi‐head attention mechanism

Wenbo Zhao, Xinghua Cheng, Dezhi Wang, Xiaodan Xiong et al. • IET Radar, Sonar & Navigation (2024)

Abstract In the field of underwater target detection, the passive sonar is an important means of long‐distance target detection. The sonar detection information typically includes both surface and underwater targets, whereas it is a great c...

DOAJ Open Access (DOAJ) DOI: 10.1049/rsn2.12653

Artificial Intelligence and Surgical Decision-making

Tyler John Loftus, Patrick James Tighe, Amanda C. Filiberto, Philip Alexander Efron et al. • JAMA Surgery (2019)

Importance: Surgeons make complex, high-stakes decisions under time constraints and uncertainty, with significant effect on patient outcomes. This review describes the weaknesses of traditional clinical decision-support systems and proposes...

OPENALEX Open Access DOI: https://doi.org/10.1001/jamasurg.2019.4917 PMC: 7286802

Optimizing Energy Consumption of Edge-Cloud Environments: A comparative Study Between PPO and PSO

Alejandro Espinosa, Xavier Samos, Daniel Ulied, Jordi Marias et al. • International Journal of Computational Intelligence Systems (2025)

Abstract As the usage of the edge-cloud continuum increases, Kubernetes presents itself as a solution that allows easy control and deployment of applications in these highly-distributed and heterogeneous environments. In this context, Artif...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44196-025-01073-2

Comparative architectural evaluation of CNN models with alternative classifiers for UAV-based detection of damaged green zones

Nodir Rakhimov, Jura Kuvandikov, Ma'ruf Tojiyev, Dilmurod Khasanov et al. • Frontiers in Artificial Intelligence (2026)

Unmanned aerial vehicle imagery provides a practical and high-resolution data source for monitoring the spatial condition of urban and peri-urban green zones. However, the reliable detection of damaged, stressed, or declining vegetation are...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1910842

Imago Imaginis

Marjana Dolšina Delač • Ars & Humanitas (2026)

Teaching formal analysis in art history often reveals gaps between students’ visual perception and their analytical articulation. This study explores the pedagogical potential of AI image generators in art history education, focusing on the...

DOAJ Open Access (DOAJ) DOI: 10.4312/ars.20.1.159-177