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Abstract Financial time series forecasting is traditionally based on historical price patterns, often overlooking exogenous and behavioral variables that can significantly affect market movements. In this study, we enhan...

Many real-life signals and, in particular, in the space physics domain, exhibit variations acrossdifferent temporal scales. Hence, their statistical momenta may depend on the time scale at which the signal is studied. To...

IntroductionVisual electrophysiology, including electroretinograms (ERG) and visual evoked potentials (VEP), provides a real-time functional assessment of retinal and post-retinal pathways, complementing structural imagi...

Abstract High-Definition Digital Terrestrial Television (HDDTT) replaces analogue, requiring further research on propagation links due to atmospheric variables potentially disrupting signals during uplink and downlink re...

Spiking neural networks (SNNs) offer a biologically inspired, energy-efficient alternative to conventional artificial neural networks (ANNs). However, deep SNNs struggle to process complex EEG signals because their spike...

"This paper presents a supervised classification method to accurately detect epileptic brain activity in real-time from electroencephalography (EEG) data. The proposed method has three main strengths: it has low computat...

Abstract Background Signal divergence and sensory preferences may cause reproductive isolation and eventually speciation between animal populations. These patterns are particularly well known in systems with acoustic or ...

This work describes the design and optimization of a printed circuit board containing a rectangular half-loop coil designed to apply radio frequency signals on micrometric diamond crystals. The structure was optimized to...

Abstract Background Abrupt declines in vegetation productivity risk irreversible transitions. However, the magnitude of such declines (abruptness)—a key determinant ranging from nonlinear reversible transitions to nonl...

Power transformers are critical components of power systems, and their safe and reliable operation is essential for both industrial and residential applications. Real-time condition monitoring and early fault detection a...

"Seizure detection plays a central role in most aspects of epilepsy care. Understanding the complex epileptic signals system is a typical problem in electroencephalographic (EEG) signal processing. This problem requires...

Chronic lymphocytic leukemia (CLL) is characterized by the progressive accumulation of clonal B lymphocytes. Proliferation occurs in lymphoid tissues upon interaction of leukemic cells with a supportive microenvironment....

We study several simplified dark matter (DM) models and their signatures at the LHC using neural networks. We focus on the usual monojet plus missing transverse energy channel, but to train the algorithms we organize the...

"Identify spike-and-waves patterns in epileptic signals is a typical problem in electroencephalographic (EEG) signal processing. In this paper we propose cross-correlation coupled with decision tree model as new method ...

This work presents a new Ultra Wide Band (UWB) beamforming fifth-order derivative Gaussian pulse transmitter with dual small Vivaldi antennas for remote acquisition of vital signals in impulse radar applications. The sys...

Abstract The current work on emotion recognition considering EEG signals has attracted significant attention due to its advantages in fields like mental health, neural computing, and human-computer interaction. Nonethele...

Abstract Accurate classification of phonocardiogram (PCG) signals is vital for the early detection of cardiovascular diseases (CVDs), a leading cause of global mortality. However, conventional machine learning and deep l...

Abstract Production safety and efficiency depends on the reliability of the critical components in industrial equipment. However, signals measured by sensors may have complicated nonlinear and long-term sequential dynami...

To develop a new strategy to target recombinant proteins to the vacuolar storage system in transgenic plants, the ability of the transmembrane and cytosolic domains of Arabidopsis receptor homology-transmembrane-RING H2-...

The electroencephalogram (EEG) is an electrophysiological monitoring method that allows us to glimpse the electrical activity of the brain. Neural oscillations patterns are perhaps the best salient feature of EEG as they...

Transient and highly regulated elevations of cytosolic Ca2+ control a variety of cellular processes. Bulk measurements using radioactive Ca2+ and the luminescent sensor aequorin have shown that in response to pheromone, ...

Underwater sensor networks are becoming an important field of re- search, because of its everyday increasing application scope. Examples of their application areas are environmental and pollution monitoring (mainly oil s...

Abstract The teleoperation of a 6 degrees-of-freedom (DOF) manipulator is one of the basic methods to extend people’s capabilities in the wide variety of applications. The master interface based on the force/torque (FT...

Background: As athletes develop, their motor patterns evolve from variable to adaptive neuromuscular control strategies, enabling precise execution of complex movements. Traditional linear biomechanical analyses of wrest...