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Abstract Deep learning (DL) is progressively popular as a viable alternative to traditional signal processing (SP) based methods for fault diagnosis. However, the lack of explainability makes DL-based fault diagnosis met...

Abstract Hydraulic systems have the characteristics of strong fault concealment, powerful nonlinear time-varying signals, and a complex vibration transmission mechanism; hence, diagnosis of these systems is a challenge. ...

Innovative terahertz waveguides are in high demand to serve as a versatile platform for transporting and manipulating terahertz signals for the full deployment of future six-generation (6G) communication systems. Metal-w...

Abstract Detecting epileptic seizures from electroencephalogram (EEG) signals presents a significant challenge due to the nonlinear and non-stationary nature of brain activity. In this study, we propose a hybrid classifi...

With the development of all-optical networks, all-optical devices have become a research hotspot in recent years. Two-dimensional materials, represented by graphene and black phosphorus, have attracted great interest in ...

Abstract Epilepsy is a chronic neurological disease that profoundly impacts patients’ daily lives. Electroencephalography (EEG) serves as a crucial tool for the clinical diagnosis of epilepsy and other brain disorders....

Photonics offers exciting opportunities for neuromorphic computing. This paper specifically reviews the prospects of integrated optical solutions for accelerating inference and training of artificial neural networks. Cal...

Background: Cardiac complications arising from diabetes mellitus manifest as structural and functional myocardial alterations independent of traditional cardiovascular risk factors. The intricate molecular underpinnings ...

With the increase in demand to Backbone networks, one became fundamental the application of new telecommunication technologies for efficient use of devices and optical links, such as xPSK modulations with dual polarizati...

Abstract Deep learning algorithms based on neural networks make remarkable achievements in machine fault diagnosis, while the noise mixed in measured signals harms the prediction accuracy of networks. Existing denoising ...

Abstract Efficient monitoring of bone milling conditions in orthopedic and neurosurgical surgery can prevent tissue, bone, and tool damage, and reduce surgery time. Current researches are mainly focused on recognizing th...

For the structural health monitoring of composite materials, data analysis technology must be very sophisticated, capable of detecting fault patterns that are multi-level and complicated. A comprehensive deep learning pa...

The technologically-relevant task of feature extraction from data performed in deep-learning systems is routinely accomplished as repeated fast Fourier transforms (FFT) electronically in prevalent domain-specific archite...

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffi...

Electroencephalography (EEG) is a crucial technique for interpreting neurocognitive functions and the underlying neural information. Despite its advantages, such as high portability, cost-effectiveness and exceptional te...

Abstract Neural circuits construct internal ‘world-models’ to guide behavior. The predictive processing framework posits that neural activity signaling sensory predictions and concurrently computing prediction-errors...

Microelectronic computers have encountered challenges in meeting all of today’s demands for information processing. Meeting these demands will require the development of unconventional computers employing alternative p...

Abstract One of the most recently developed wireless technologies is Radio Tomographic Imaging (RTI). RTI employs a wireless sensor network that produces images of the change in the electromagnetic field of a monitored a...

To achieve an optimal trade-off between processing efficiency and dimensional precision in the assisted electrode electrochemical discharge machining (AE-ECDM) of thermal barrier coating (TBC)-coated superalloys, a 1D co...

Free-space optical (FSO) communication using dual-polarization self-coherent (DP-SC) transceivers is a promising solution for achieving high data rates and enhanced spectral efficiency in the next optical wireless system...

We review a novel paradigm that has emerged in analogue neuromorphic optical computing. The goal is to implement a reservoir computer in optics, where information is encoded in the intensity and phase of the optical fiel...

Gesture recognition plays a significant role in human-machine interaction (HMI) system. This paper proposes a gesture-controlled reconfigurable metasurface system based on surface electromyography (sEMG) for real-time be...

As society’s appetite for information continues to grow, so does our need to process this information with increasing speed and versatility. Many believe that the one-size-fits-all solution of digital electronics is be...

After an earthquake, numerous buildings are destroyed, and the frequency of structural collapses increases significantly in regions lacking comprehensive geophysical surveys. Furthermore, the number of deaths increases d...