Most Cited

The development of robust circuit structures remains a pivotal milestone in electronic device research. This article proposes an integrated hardware–software system designed for the acquisition, processing, and analysis of surface electromyogra...

Recent developments in machine learning algorithms are playing a significant role in wireless communication and Internet of Things (IoT) systems. Location-based Internet of Things services (LBIoTS) are considered one of the primary applications among...

This paper investigates the use of micro-Doppler spectrogram signatures of flying targets, such as drones and birds, to aid in their remote classification. Using a custom-designed 10-GHz continuous wave (CW) radar system, measurements from different...

Emergency Communication Systems (ECS) are network-based systems that may enable people to exchange information during crises and physical disasters when basic communication options have collapsed. They may be used to restore communication in off-grid...

Nutrition plays a fundamental role in promoting health and preventing chronic diseases, with bioactive food components offering a therapeutic potential in biomedical applications. Among these, edible oils are recognised for their functional propertie...

The swift advancement of quantum computing devices holds the potential to create robust machines that can tackle an extensive array of issues beyond the scope of conventional computers. Consequently, quantum computing machines create new risks at a v...

Epilepsy is a complex neurological disorder characterized by recurrent and unpredictable seizures that affect millions of people around the world. Early and accurate epilepsy detection is critical for timely medical intervention and improved patient...

An innovative treatment for congested urban road networks is the split intersection. Here, a congested two-way–two-way traffic light-controlled intersection is transformed into two lighter intersections. By reducing conflict points and improvin...

Structural deterioration is a primary long-term concern resulting from material wear and tear, events, solicitations, and disasters that can progressively compromise the integrity of a cement-based structure until it suddenly collapses, becoming a po...

Rainfall information with high spatial and temporal resolution are essential in various fields. Heavy rainfall in a short period can cause problems and disasters that result in loss of life and damage to property. Conversely, the absence of rain for...

Early detection and evaluation of children at risk of neurodevelopmental disorders and/or communication deficits is critical. While the current literature indicates a high prevalence of neurodevelopmental disorders, many children remain undiagnosed,...

Effective management of EEG artifacts is pivotal for accurate neurological diagnostics, particularly in detecting early stages of Alzheimer’s disease. This review delves into the cutting-edge domain of fuzzy logic techniques, emphasizing intuit...

In brain–computer interface motor imagery (BCI-MI) systems, convolutional neural networks (CNNs) have traditionally dominated as the deep learning method of choice, demonstrating significant advancements in state-of-the-art studies. Recently, T...

Change detection in biomedical signals is crucial for understanding physiological processes and diagnosing medical conditions. This study evaluates various change detection methods, focusing on synthetic signals that mimic real-world scenarios. We ex...

Breast cancer is the most common cancer in women, a leading cause of morbidity and mortality, and a significant health issue worldwide. According to the World Health Organization’s cancer awareness recommendations, mammographic screening should...

X-ray photoelectron spectroscopy (XPS) remains a fundamental technique in materials science, offering invaluable insights into the chemical states and electronic structure of a material. However, the interpretation of XPS spectra can be complex, requ...

Speech Emotion Recognition (SER) technology helps computers understand human emotions in speech, which fills a critical niche in advancing human–computer interaction and mental health diagnostics. The primary objective of this study is to enhan...

Air quality is a subject of study, particularly in densely populated areas, as it has been shown to affect human health and the local ecosystem. In recent years, with the rapid development of technology, low-cost sensors have emerged, with many peopl...

The goal of this study is to explore the effectiveness of applying multi-objective particle swarm optimization (MOPSO) algorithms in the design of infinite impulse response (IIR) filters. Given the widespread application of IIR filters in digital sig...

Predicting rock bursts is essential for maintaining worker safety and the long-term growth of subsurface infrastructure. The purpose of this study is to investigate the precursor reactions and processes of rock instability. To determine the degree of...

Infant electrocardiograms (ECGs) and heart rates (HRs) are very useful biosignals for psychological research and clinical work, but can be hard to analyse properly, particularly longform (≥5 min) recordings taken in naturalistic environments. Infa...

In gasoline engines, the combustion process involves a flame’s propagation from the spark plug to the cylinder walls, resulting in the localized heating and pressurization of the cylinder content ahead of the flame, which can lead to the autoig...

Within the broad problem known as automatic music transcription, we considered the specific task of automatic drum transcription (ADT). This is a complex task that has recently shown significant advances thanks to deep learning (DL) techniques. Most...

Mobile networks of the fifth generation have stringent requirements for data throughput, latency and reliability. Dual or multi-connectivity is implemented to meet the mobility requirements for certain essential 5G use cases, and this ensures the use...

Currently, Internet of Things (IoT) has become common in various applications, including smart factories, smart cities, and smart homes. In them, wireless local-area networks (WLANs) are widely used due to their high-speed data transfer, flexible cov...

Reliable streamflow forecasting is crucial for several tasks related to water-resource management, including planning reservoir operations, power generation via Hydroelectric Power Plants (HPPs), and flood mitigation, thus resulting in relevant socia...

Acute psychological stress (APS) is a complex and multifactorial phenomenon that affects metabolism, necessitating real-time detection and interventions to mitigate its effects on glycemia in people with type 1 diabetes. This study investigates the d...

Treadmill running simulates various conditions, including flat, uphill, and downhill gradients, making it useful for training and rehabilitation. This study aimed to examine how incline and decline treadmill running affect local dynamic stability of...

We consider the challenge of detecting and clustering point and collective anomalies in streaming data that exhibit significant nonlinearities and seasonal structures. The challenge is motivated by detecting problems in a communications network, wher...

In this work, an effective Fault Detection and Diagnosis (FDD) strategy designed to increase the performance and accuracy of fault diagnosis in grid-connected photovoltaic (GCPV) systems is developed. The evolved approach is threefold: first, a pre-p...

In this paper, we propose robust image-smoothing methods based on ${\mathit{\ell }}_0$ gradient minimization with novel gradient constraints to effectively suppress pseudo-edges. Simultaneously minimizing the ${\mathit{\ell }}_0$ gradient, i.e., the number of nonzero gradie...

In biomedical engineering, Information Theory Quantifiers (ITQs) are used to analyze diseases by evaluating bioelectrical signals. This review article presents a meta-analysis to highlight the knowledge gap regarding the various perspectives and exis...

Analyzing brain activity during mental arithmetic tasks provides insight into psychological disorders such as ADHD, dyscalculia, and autism. While most research is conducted on the static functional connectivity of the brain while performing a cognit...

Deep learning models, particularly transformer architectures, have revolutionized various computer vision tasks, including image classification. However, their performance under different types and levels of noise remains a crucial area of investigat...

The first meter-scale interstellar meteor (IM1) was detected by US government sensors in 2014, identified as an interstellar object candidate in 2019, and confirmed by the Department of Defense (DoD) in 2022. We use data from a nearby seismometer to...

Dynamic mode decomposition (DMD) is a powerful tool for separating the background and foreground in videos. This algorithm decomposes a video into dynamic modes, called DMD modes, to facilitate the extraction of the near-zero mode, which represents t...

Confusion emotion in a learning environment can motivate the learner, but prolonged confusion hinders the learning process. Recognizing confused learners is possible; nevertheless, finding them requires a lot of time and effort. Due to certain restri...

Electroencephalographic (EEG) monitoring is important for the diagnosis of hypoxic-ischemic (HI) brain injury in high-risk preterm infants. EEG monitoring is limited by the reliance on expert clinical observation. However, high-risk preterm infants o...

Accurate teeth segmentation and orientation are fundamental in modern oral healthcare, enabling precise diagnosis, treatment planning, and dental implant design. In this study, we present a comprehensive approach to teeth segmentation and orientation...

Computer-based job interview training, including virtual reality (VR) simulations, have gained popularity in recent years to support and aid autistic individuals, who face significant challenges and barriers in finding and maintaining employment. Alt...

Reliable prognostic biomarkers are needed to support the early diagnosis of brain injury in extremely preterm infants, and to develop effective neuroprotective protocols that are tailored to the progressing phases of injury. Experimental and clinical...

Several factors impact the durability of concrete bridge decks, including traffic loads, fatigue, temperature changes, environmental stress, and maintenance activities. Detecting problems such as corrosion, delamination, or concrete degradation early...

We present an algorithm for extracting basis functions from the chaotic Lorenz system along with timing and bit-sequence statistics. Previous work focused on modifying Lorenz waveforms and extracting the basis function of a single state variable. Imp...

This paper presents a study of an automated system for identifying planktic foraminifera at the species level. The system uses a combination of deep learning methods, specifically convolutional neural networks (CNNs), to analyze digital images of for...

Brain responses to discrete stimuli are modulated when multiple stimuli are presented in sequence. These alterations are especially pronounced when the time course of an evoked response overlaps with responses to subsequent stimuli, such as in a rapi...

The implementation of a machine learning approach to predict vibration suppression, as derived from nanocomposite laminates with piezoelectric shunted systems, is studied in this article. Datasets providing the vibration response and vibration attenu...

Due to the escalating network throughput and security risks, the exploration of intrusion detection systems (IDSs) has garnered significant attention within the computer science field. The majority of modern IDSs are constructed using deep learning t...

Neural networks have inductive biases owing to the assumptions associated with the selected learning algorithm, datasets, and network structure. Specifically, convolutional neural networks (CNNs) are known for their tendency to exhibit textural biase...

Modern healthcare systems are under growing strain from aging populations, urbanization, and rising chronic disease burdens, creating an urgent need for real-time monitoring and informed decision-making. This survey examines how the convergence of In...

Pick-and-place operations are an integral part of robotic automation and smart manufacturing. By utilizing deep learning techniques on resource-constraint embedded devices, the pick-and-place operations can be made more accurate, efficient, and susta...