Automatic recognition methods for non-stationary electroencephalogram (EEG) data collected from EEG sensors play an essential role in neurological detection. The integrated approaches proposed in this study consist of Symlet wavelet processing, a gra...
Today, cardiovascular disease is the leading cause of death in developed countries. The most common arrhythmia is atrial fibrillation, which increases the risk of ischemic stroke. An electrocardiogram is one of the best methods for diagnosing cardiac...
Wavelet transformation is one of the most frequent procedures for data denoising, smoothing, decomposition, features extraction, and further related tasks. In order to perform such tasks, we need to select appropriate wavelet settings, including part...
This paper presents a comparative study on mother wavelets using a fault type classification algorithm in a power system. The study aims to evaluate the performance of the protection algorithm by implementing different mother wavelets for signal anal...
The detection of cracked railway axles by processing vibratory signals measured during operation is the focus of this study. The rotodynamic theory is applied to this specific purpose but, in practice and for real systems, there is no consensus on ap...
The aim of this paper is to find the optimal mother wavelet function and wavelet decomposition level when denoising the Doppler cardiogram (DCG), the heart signal obtained by the Doppler radar sensor system. To select the best suited mother wavelet f...
Magnetic Resonance Imaging (MRI) is a noninvasive technique used in medical imaging to diagnose a variety of disorders. The majority of previous systems performed well on MRI datasets with a small number of images, but their performance deteriorated...
In this paper, a new method was introduced for feature extraction and fault diagnosis in bearings based on wavelet packet decomposition and analysis of the energy in different frequency bands. This method decomposes a signal into different frequency...
The operational challenge of a photovoltaic (PV) integrated system is the uncertainty (irregularity) of the future power output. The integration and correct operation can be carried out with accurate forecasting of the PV output power. A distinct art...
Wavelet transformation has been widely used in geophysical and geochemical exploration, and the fractal feature of wavelet coefficients has recently stood out from many wavelet threshold methods. We introduced the wavelet–fractal method to anal...
Improving the accuracy of cash flow forecasting in the TSA is key to fulfilling government payment obligations, minimizing the cost of maintaining the cash reserve, providing the absence of outstanding debt accumulation and ensuring investment in fin...
This study focuses on identifying damage in reinforced concrete (RC) beams using time-domain modal testing and wavelet analysis. A numerical model of an RC beam was used to generate various damage scenarios with different severities and locations. Ac...
In recent years, skin cancer diagnosis has been aided by the most sophisticated and advanced machine learning algorithms, primarily implemented in the spatial domain. In this research work, we concentrated on two crucial phases of a computer-aided di...
As higher spatiotemporal resolution tactile sensing systems are being developed for prosthetics, wearables, and other biomedical applications, they demand faster sampling rates and generate larger data streams. Sparsifying transformations can allevia...
We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM) task recorded through electro...
The North Atlantic Oscillation (NAO) represents the dominant atmospheric mode governing climate variability across the Northern Hemisphere, particularly influencing precipitation regimes in regions such as northern Algeria. This study investigates th...
Watermarking is currently investigated as an efficient and safe method of embedding additional patient or environment-related data into the electrocardiogram. This paper presents experimental work on the assessment of the loss of ECG (electrocardiogr...
Detection rapidity and model accuracy are the keys to hyperspectral nondestructive testing technology, especially for Pennisetum sinese Roxb (PsR) due to its extremely high adsorptive heavy metal content. The study of the resolution of PsR is conduci...
The control of thermostats of a heating, ventilation, and air-conditioning (HVAC) system installed in commercial and residential buildings remains a pertinent problem in building energy efficiency and thermal comfort research. The ability to determin...
Video-based human activity recognition (HAR) means the analysis of motions and behaviors of human from the low level sensors. Over the last decade, automatic HAR is an exigent research area and is considered a significant concern in the field of comp...
The growing demand for electricity, integration of renewable energy sources, and recent advances in power electronics have driven the development of HVDC systems. Multi-terminal HVDC (MTDC) grids, enabled by Voltage Source Converters (VSCs), provide...
Soil moisture is an important factor determining yield. With the increasing demand for agricultural irrigation water resources, evaluating soil moisture in advance to create a reasonable irrigation schedule would help improve water resource utilizati...
The early detection and prevention of plant diseases that are an important cause of famine and food insecurity worldwide are very important for increasing agricultural product productivity. Not only the early detection of the plant disease but also t...
Recent research in the field of cognitive motor action decoding focuses on data acquired from Functional Near-Infrared Spectroscopy (fNIRS) and its analysis. This research aims to classify two different motor activities, namely, mental drawing (MD) a...
Background/Objectives: This article addresses the challenge of stress detection across diverse contexts. Mental stress is a worldwide concern that substantially affects human health and productivity, rendering it a critical research challenge. Althou...