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A Scalo Gram-Based CNN Ensemble Method With Density-Aware SMOTE Oversampling for Improving Bearing Fault Diagnosis

Muhammad Irfan, Zohaib Mushtaq, Nabeel Ahmed Khan, Salim Nasar Faraj Mursal et al. • IEEE Access (2023)

Machine learning (ML) based bearing fault detection is an emerging application of Artificial Intelligence (AI) that has proven its utility in effectively classifying various faults for timely measures. There are myriad studies dedicated to ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3332243

IEEE Access Special Section Editorial: 5G and Beyond Mobile Wireless Communications Enabling Intelligent Mobility

Ke Guan, Markus Rupp, Thomas Kurner, Cesar Briso et al. • IEEE Access (2020)

Increasing urbanization is one major trend that shapes tomorrow’s society; by 2050, more than 85% of the developed world’s population will live in a comparatively small number of ever-growing cities. Within such cities ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3037635

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

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

A bibliometric analysis of industry 4.0 digital manufacturing and smart technologies for sustainable development

Ferhat Yilmaz, Zeynep Ozguner • Discover Sustainability (2026)

Abstract This study provides a broad bibliometric analysis of Industry 4.0 as well as technology-based production systems within the appropriate scientific literature to target the description of the dynamic structure, intellectual foundati...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43621-026-03275-w

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

<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: The Basics

Kevin Warwick • Routledge eBooks (2013)

'if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intel...

OPENALEX DOI: https://doi.org/10.4324/9780203802878

Artificial intelligence

Igor Aleksander • Electronics and Power (1976)

The dividing line between pattern recognition and artificial intelligence is very slim. Consequently, the pattern-recognition ability of the random-access memory can be utilised in implementing networks of high ‘intelligence’...

OPENALEX DOI: https://doi.org/10.1049/ep.1976.0108

Artificial Intelligence in Education: A Review

Lijia Chen, Pingping Chen, Zhijian Lin • IEEE Access (2020)

The purpose of this study was to assess the impact of Artificial Intelligence (AI) on education. Premised on a narrative and framework for assessing AI identified from a preliminary analysis, the scope of the study was limited to the applic...

OPENALEX cc-by DOI: https://doi.org/10.1109/access.2020.2988510

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

Timor Leste in ASEAN: Implications for ASEAN-Led Economic Multilateralism in the Digital Field

Evgeny A. Kanaev • Vestnik RUDN. International Relations (2026)

The paper explores the main implications of East Timor’s accession to the Association of Southeast Asian Nations (ASEAN) in October 2025 for ASEAN-led economic projects and initiatives in the digital field. The research aims to identify the...

DOAJ Open Access (DOAJ) DOI: 10.22363/2313-0660-2026-26-3-476-488

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

Detection and Classification of Abnormities of First Heart Sound Using Empirical Wavelet Transform

Haixia Li, Yongfeng Ren, Guojun Zhang, Renxin Wang et al. • IEEE Access (2019)

It is expected that an automatic detection and classification algorithm for the abnormities of first heart sound (S1) can realize computer artificial intelligence diagnosis of some relative cardiovascular disease. Few studies have focused o...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2943705