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Materias / palabras clave: Psychophysics; Detection theory; SIGNAL (programming language); Computer science; Psychology; Telecommunications; Neuroscience; Perception; Detector; Programming language

This paper presents the application of Signal Detection Theory (SDT) concepts to the certification of optional systems that provide operational or system safety benefits. The method and analysis yield quantitative requir...

To detect internal valve leakage in liquid-filled pipelines, a method using kernel principal component analysis (KPCA) is proposed to analyze acoustic emission (AE) signals for leakage detection. Time-frequency analysis ...

Bacteria of the genus Bradyrhizobium are able to establish a symbiotic relationship with peanut (Arachis hypogaea) root cells and to fix atmospheric nitrogen by converting it to nitrogenous compounds. Quorum sensing (QS)...

ABSTRACT The growing demand for rare‐earth elements (REEs), particularly dysprosium (Dy), underscores the need for sustainable extraction methods. Recovery of Dy, particularly from geographically distributed waste sour...

Abstract This paper presents an eyebolt structural fault detection system, based on the analysis of multiple electromagnetic parameters through a random forest classifier trained by both measurements and high-fidelity si...

Duck adenovirus 3 (DAdV-3) was firstly identified in Muscovy ducklings exhibiting slight pericardial effusion, swelling, and hemorrhaging in the kidneys, which is a poorly characterized duck virus. This study established...

The identification of exoplanets within habitable zones remains a central objective in modern astrophysics, particularly with the availability of large-scale photometric datasets from space-based missions such as the Tra...

The genome of one equine embryo and three equine semen specimens collected from a Brazilian farm were tested by polymerase chain reaction (PCR) for the presence of EHV-1 and EHV-4-specific timidine kinase (TK) sequences....

"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...

Abstract Brucellosis is a common zoonotic disease caused by Brucella and remains a globally concerning public health issue. Timely and effective detection methods are crucial for clinical diagnosis. We developed a novel ...

Abstract The zero forcing (ZF) and the and minimum mean square error (MMSE) conventional algorithms has been widely employed as near-optimal detectors for large-scale multiple-input multiple-output (LS-MIMO) systems, whe...

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....

Reliable beat-level arrhythmia detection from electrocardiogram (ECG) signals is essential for continuous patient monitoring. However, many existing deep learning models remain computationally expensive and are sensitive...

Abstract We propose a continuous stress-detection pipeline that integrates wavelet-based heart-rate-variability (HRV) features with behavioural signals in a staged ensemble. The method computes time-resolved HRV spectral...

Infrared thermal radiation signals are highly susceptible to environmental interference, leading to dynamic fluctuations. Consequently, weak targets are frequently submerged in heavy clutter backgrounds under extreme sce...

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...

This research describes a deep learning-based artificial neural network (ANN) approach for the detection, classification, and localization of series faults (open conductor faults) in power distribution networks. The ANN ...

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...

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...

In this study, we experimentally showcase the microfiber evanescent-field photothermal gas detection by exploiting all-fiber MHz-level frequency shift scheme. Based on the acousto-optic interaction effect, the low-freque...

Optical interconnects, leveraging surface plasmon modes, are revolutionizing high-performance computing and AI, overcoming the limitations of electrical interconnects in speed, energy efficiency, and miniaturization. The...

This paper describes an application of the ground penetrating radar (GPR) method for detecting pipe flanges. A case history is described in which GPR was successfully used to locate pipe flanges along an 8 km metal pipel...

Epilepsy is a chronic neurological disorder of the brain that affects around 50 million people worldwide. The early detection of epileptic seizures using electroencephalogram (EEG) signals is a useful tool for several ap...