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Showing 20 of 234 academic articles

Generative-Adversarial-Network-Based Image Reconstruction for the Capacitively Coupled Electrical Impedance Tomography of Stroke

Mikhail Ivanenko, Damian Wanta, Waldemar T. Smolik, Przemysław Wróblewski et al. • Life (2024)

This study investigated the potential of machine-learning-based stroke image reconstruction in capacitively coupled electrical impedance tomography. The quality of brain images reconstructed using the adversarial neural network (cGAN) was e...

DOAJ Open Access (DOAJ) DOI: 10.3390/life14030419

Hybrid-Timescale Physics-Informed Neural Network for Electrical Equivalent Impedance Identification in Induction Heating Systems

Oscar Lahuerta, Claudio Carretero, Luis Angel Barragan, Denis Navarro et al. • IEEE Open Journal of the Industrial Electronics Society (2026)

This article introduces a hybrid variant of a physics-informed neural network (PINN) that is designed to effectively capture both the rapid dynamics of electrical variables and the slower dynamics of state parameters in a domestic induction...

DOAJ Open Access (DOAJ) DOI: 10.1109/OJIES.2026.3663897

Q-Learning Based Joint Energy-Spectral Efficiency Optimization in Multi-Hop Device-to-Device Communication

Muhidul Islam Khan, Luca Reggiani, Muhammad Mahtab Alam, Yannick Le Moullec et al. • Sensors (2020)

In scenarios, like critical public safety communication networks, On-Scene Available (OSA) user equipment (UE) may be only partially connected with the network infrastructure, e.g., due to physical damages or on-purpose deactivation by the ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s20226692

Trinity: In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics

Ji-Hoon Kim, Seunghee Han, Kwanghyun Park, Soo-Young Ji et al. • IEEE Access (2024)

The ability to perform machine learning (ML) tasks in a database management system (DBMS) is a new paradigm for conventional database systems as it enables advanced data analytics on top of well-established capabilities of DBMSs. However, t...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3347725

Accelerated Prediction of Terahertz Performance Metrics in GaN IMPATT Sources via Artificial Neural Networks

Santu Mondal, Sneha Ray, Aritra Acharyya, Rudra Sankar Dhar et al. • IEEE Access (2025)

This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regim...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3567410

Memristor Synapse—A Device-Level Critical Review

Sridhar Chandrasekaran, Yao-Feng Chang, Firman Mangasa Simanjuntak • Nanomaterials (2026)

The memristor has long been known as a nonvolatile memory technology alternative and has recently been explored for neuromorphic computing, owing to its capability to mimic the synaptic plasticity of the human brain. The architecture of a m...

DOAJ Open Access (DOAJ) DOI: 10.3390/nano16030179

Evaluation of Predictive Maintenance by Marginal Utility: A Case Study on Offshore Wind

Rasmus Dovnborg Frederiksen, Grzegorz Radzki, Grzegorz Bocewicz, Peter Nielsen et al. • Applied Sciences (2026)

This paper investigates the relationship between the benefits achieved by predictive maintenance implementation and the related costs incurred intentionally or not. Specifically, we seek to establish an evaluation method for predictive main...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16178708

An intelligent machine learning paradigm for gyrotactic micro-organism-induced squeezing flow of Eyring–Powell hybrid nanofluids with entropy generation

A. Imran, Muna Elsadig, Jongsuk Ro • AIP Advances (2026)

A novel unsteady squeezing flow of a non-Newtonian ternary hybrid nanofluid is investigated by focusing Eyring–Powell fluid rheology in an infinite channel. The nanofluid consists of AA1072, AA1075, and ZrO2 nanoparticles suspended in blood...

DOAJ Open Access (DOAJ) DOI: 10.1063/5.0337148

Advancing Biosensors with Machine Learning

Feiyun Cui, Yun Yue, Yi Zhang, Ziming Zhang et al. • ACS Sensors (2020)

Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, es...

OPENALEX DOI: https://doi.org/10.1021/acssensors.0c01424

A flexible analytic wavelet transform and ensemble bagged tree model for electroencephalogram-based meditative mind-wandering detection

Ajay Dadhich, Jaideep Patel, Rovin Tiwari, Richa Verma et al. • Healthcare Analytics (2024)

Mind-wandering (MW) is when an individual’s concentration drifts away from the task or activity. Researchers found a greater variability in electroencephalogram (EEG) signals due to MW. Collecting more nuanced information from raw EEG data ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.health.2023.100286

Artificial intelligence

S. Pradeesh Hosea, V. Harikrishnan, K. Rajkumar • International Conference on Electronics Computer Technology (2011)

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on repres...

OPENALEX DOI: https://doi.org/10.1109/icectech.2011.5941871

A Novel Approach for Multichannel Epileptic Seizure Classification Based on Internet of Things Framework Using Critical Spectral Verge Feature Derived from Flower Pollination Algorithm

Dhanalekshmi Prasad Yedurkar, Shilpa P. Metkar, Fadi Al-Turjman, Thompson Stephan et al. • Sensors (2022)

A novel approach for multichannel epilepsy seizure classification which will help to automatically locate seizure activity present in the focal brain region was proposed. This paper suggested an Internet of Things (IoT) framework based on a...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22239302

Artificial intelligence

Akshar Joshi, Gautam Mishra • International Conference & Workshop on Emerging Trends in Technology (2010)

In this paper, we will explore the magic of giving the power of thinking to man--made machines, i.e. Artificial Intelligence which is involved in many fields of electronics and computers. In 1956, John McCarthy who coined the term of Artifi...

OPENALEX DOI: https://doi.org/10.1145/1741906.1742236

Explainable artificial intelligence: A survey

Filip Karlo Došilović, Mario Brčić, Nikica Hlupić • International Convention on Information and Communication Technology, Electronics and Microelectronics (2018)

In the last decade, with availability of large datasets and more computing power, machine learning systems have achieved (super)human performance in a wide variety of tasks. Examples of this rapid development can be seen in image recognitio...

OPENALEX DOI: https://doi.org/10.23919/mipro.2018.8400040

An Overview of Artificial Intelligence Applications for Power Electronics

Shuai Zhao, Frede Blaabjerg, Huai Wang • IEEE Transactions on Power Electronics (2020)

This is a preprint version of the manuscript submitted to IEEE on June 4, 2020. This paper gives an overview of the Artificial Intelligence (AI) applications for power electronic systems. The three distinctive life-cycle phases, design, con...

OPENALEX cc-by DOI: https://doi.org/10.1109/tpel.2020.3024914