Frequency-based leak signature investigation using acoustic sensors in urban water distribution networks

K Sitaropoulos, S Salamone, L Sela - Advanced Engineering Informatics, 2023 - Elsevier
Cities worldwide have been plagued by water pipe leaks for many decades, resulting in
financial losses, public health risks, and environmental impacts. Current practice still relies …

Antagonistic behavior of brain networks mediated by low-frequency oscillations: electrophysiological dynamics during internal–external attention switching

J Hammer, M Kajsova, A Kalina, D Krysl… - Communications …, 2024 - nature.com
Antagonistic activity of brain networks likely plays a fundamental role in how the brain
optimizes its performance by efficient allocation of computational resources. A prominent …

An efficient deep learning framework for P300 evoked related potential detection in EEG signal

P Havaei, M Zekri, E Mahmoudzadeh… - Computer Methods and …, 2023 - Elsevier
Background Incorporating the time-frequency localization properties of Gabor transform
(GT), the complexity understandings of convolutional neural network (CNN), and histogram …

A Unified Transformer-based Network for Multimodal Emotion Recognition

K Ali, CE Hughes - arXiv preprint arXiv:2308.14160, 2023 - arxiv.org
The development of transformer-based models has resulted in significant advances in
addressing various vision and NLP-based research challenges. However, the progress …

Deep-Learning-Based Classification of Cyclic-Alternating-Pattern Sleep Phases

Y Kahana, A Aberdam, A Amar, I Cohen - Entropy, 2023 - mdpi.com
Determining the cyclic-alternating-pattern (CAP) phases in sleep using
electroencephalography (EEG) signals is crucial for assessing sleep quality. However, most …

Towards automated pipelines for processing load test data on a HS railway bridge in Spain using a digital twin

C Ramonell, R Chacón - ISARC. Proceedings of the …, 2022 - search.proquest.com
This document presents an automated pipeline to process sensor-based data produced
during load tests on digitally twinned HS railway bridges. The research is developed within …

Classifying LPI radar waveforms with time-frequency transformations using multi-stage CNN system

I Guven, C Yagmur, B Karadas… - 2022 23rd International …, 2022 - ieeexplore.ieee.org
As the number of radar waveforms in the cognitive electronic warfare applications increases,
individual detection and classification performances of each waveform vary furthermore due …

U-ENHANCE: Underwater Image Enhancement Using Wavelet Triple Self-Attention

P Mishra, SK Vipparthi… - Proceedings of the Asian …, 2024 - openaccess.thecvf.com
Transformer-based methods have demonstrated remarkable performance in underwater
image enhancement due to their ability to capture long-range dependencies, crucial for high …

Fault classification and localization in microgrids: Leveraging discrete wavelet transform and multi-machine learning techniques considering single point …

BG Basher, A Ghanem, S Abulanwar… - Electric Power Systems …, 2024 - Elsevier
Currently, microgrids are becoming more prevalent. Therefore, it is crucial to develop robust
and reliable microgrid protection schemes. Researchers have recently explored various …

Helical Gearbox Defect Detection with Machine Learning Using Regular Mesh Components and Sidebands

I Lupea, M Lupea, A Coroian - Sensors, 2024 - mdpi.com
The current paper presents helical gearbox defect detection models built from raw vibration
signals measured using a triaxial accelerometer. Gear faults, such as localized pitting …