Automatic emotion recognition based on EEG has been a key research frontier in recent years, involving the direct extraction of emotional states from brain dynamics. However, existing deep learning approaches often treat EEG either as a sequence or a...
Despite successful revascularization, patients with non-ST elevation myocardial infarction (NSTEMI) remain at higher risk of mortality and morbidity. Accurately predicting mortality risk in this cohort can improve outcomes through timely intervention...
Foreground segmentation and background subtraction are critical components in many computer vision applications, such as intelligent video surveillance, urban security systems, and obstacle detection for autonomous vehicles. Although extensively stud...
Feature extraction and description are fundamental components of visual perception systems used in applications such as visual odometry, Simultaneous Localization and Mapping (SLAM), and autonomous navigation. In resource-constrained platforms, such...
Multitrack music transcription is the task of converting music recordings into symbolic music representations that are assigned to individual instruments. This task requires simultaneous transcription of note onset and offset events for individual in...
With rapid advances in nanotechnology and synthetic biology, biological nanonetworks are emerging for biomedical and environmental applications within the Internet of Bio-NanoThings. While they rely on molecular communication, experimental validation...
Bearing fault diagnosis is critical in rotating machinery, and collecting and analyzing vibration signals from faulty bearings is a widely employed method in fault diagnosis. To efficiently extract the information of periodic pulse from complex signa...
This paper focuses on the design of robust fusion estimators for multi-sensor systems experiencing constrained communications, model uncertainties, and random packet dropouts. To mitigate the impact of modeling errors, a sensitivity-penalized robust...
This survey delves into the Firebug Swarm Optimization (FSO) algorithm, an advanced global optimization algorithm that plays a pivotal role in modern swarm intelligence optimization techniques. It explores the core principles of the FSO algorithm and...
Self-supervised learning (SSL) models have achieved remarkable success in speaker verification tasks, yet their robustness to real-world audio degradation remains insufficiently characterized. This study presents a comprehensive analysis of how audio...
To obtain radar images of a group of small space objects or to resolve individual elements of complex space objects in near-Earth orbit, a radar system must have high spatial resolution. High range resolution is achieved by using complex probing sign...
Leg dominance has been linked to an increased risk of lower-limb injuries in sports. This study examined bilateral asymmetry in muscle synergy patterns during one-leg stance on stable and multiaxial unstable surfaces. Twenty-five active young adults...
Background and Objective: The accurate detection of sleep stages and disorders in older adults is essential for the effective diagnosis and treatment of sleep disorders affecting millions worldwide. Although Polysomnography (PSG) remains the primary...
The absence of a recognizable P wave in an electrocardiogram (ECG) is a critical indicator for the diagnosis of atrial fibrillation (AF). An algorithm capable of distinguishing between physiological and pathological states in a short period of time c...
Scene depth information is a key component of any robotic mobile application. Range sensors, such as LiDAR, sonar, or radar, capture depth data of a scene. However, the data captured by these sensors frequently presents missing regions or information...
Autonomous vehicles (AVs) are transforming transportation by improving safety, efficiency, and intelligence through integrated sensing, computing, and communication technologies. However, their growing reliance on Vehicle-to-Everything (V2X) communic...
The safe and stable operation of power systems and other dynamic systems relies on accurate perception of their dynamic processes. Voltage, current, and other measurement signals carry critical information about the system’s state. However, und...
This paper presents a comparative analysis of the influence of Fused Deposition Modeling (FDM) parameters—specifically material type, infill geometry, and density—on the vibro-acoustic characteristics of loudspeaker enclosures. The enclos...
Remote photoplethysmography (rPPG) enables non-contact heart rate estimation but remains highly sensitive to illumination variation and dataset-dependent factors. This study proposes CHROM-Y, a robust 2D feature representation that combines chrominan...
This study evaluates Empirical Bayes (EB) c-charts for monitoring count-type data under precautionary (PLF) and logarithmic (LLF) loss functions. By assuming an exponential prior for the Poisson mean, the EB framework enables the construction of pred...
The wavelet transform (WT) is an integral transform primarily used for processing and analyzing nonstationary signals due to its multiresolution property. Multiresolution analysis is one method that finds applications in many fields because of the ch...
Second-order notch filters (NFs) with constant coefficients are often used as part of feedback controllers in grid-connected power conversion systems to prevent unwanted harmonic content polluting the closed control loops. In practice, the value of t...
Muscle synergies offer valuable insights into the movement strategies employed by the central nervous system and present a promising avenue for clinical applications. However, the field lacks a complete understanding of how surface electromyography p...
Monitoring physiological activity and sleep states in real time is challenging, particularly for continuous assessment in daily life settings using wearable IoMT devices. We developed a 24 h wearable system that integrates electrocardiogram (ECG) ele...
Foot gesture recognition using a continuous-wave (CW) radar requires implementation on edge hardware with strict latency and memory budgets. Existing structured and unstructured pruning pipelines rely on iterative training–pruning–retrain...
This paper presents a novel methodology for the design and calibration of ultra-compact digital-to-analog converters (DACs), integrating architectural redundancy and a digital calibration algorithm. The proposed calibration approach generates pre-dis...
We propose a novel hybrid deep learning framework that synergistically integrates Convolutional Neural Networks (CNNs), Spiking Neural Networks (SNNs), and Generative Adversarial Networks (GANs) for robust and accurate classification of high-resoluti...
To address the demand for lightweight, high-precision, real-time, and low-computation detection of targets with limited samples—such as laboratory instruments in portable AR devices—this paper proposes a small dataset object detection alg...
An electrocardiogram (ECG) is a vital diagnostic tool that provides crucial insights into the heart rate, cardiac positioning, origin of electrical potentials, propagation of depolarization waves, and the identification of rhythm and conduction irreg...
Myocardial infarction (MI) remains one of the most critical causes of death worldwide, demanding predictive models that balance accuracy with clinical interpretability. This study introduces an explainable artificial intelligence (XAI) framework that...
The early detection of smoke signals due to wildfires is vital in containing the extent of loss and reducing response time, particularly in inaccessible or forested areas. For lightweight object detection, this study contrasts the YOLOv9-tiny, YOLOv1...
Human action recognition (HAR) based on WiFi channel state information (CSI) has attracted growing attention due to its contactless, privacy-preserving, and cost-effective nature. Recent studies have reported promising results by leveraging deep lear...
Ham radio has long been a foundational area of practice in electrical engineering. Advances in signal processing, particularly the advent of software-defined radio (SDR), have revolutionized the field, offering new possibilities and modes of operatio...
Burst traffic radio systems use short signal bursts, which are prepended with an a priori known preamble sequence. The burst receivers exploit these preamble sequences for burst start detection. The process of burst start detection is commonly known...
Acoustic scattering is a highly effective tool for non-destructive control and structural analysis. In many real-world applications, understanding acoustic scattering is essential for accurately detecting and characterizing defects, assessing materia...
This study presents a method for deriving closed-form solutions for Lagrange multipliers in worst-case performance optimization (WCPO) beamforming. By approximating the array-received signal autocorrelation matrix as a rank-1 Hermitian matrix using t...
This study investigated the transformative potential of Compressive Sensing (CS) for optimizing multimodal biomedical signal fusion in Wireless Body Sensor Networks (WBSN), specifically targeting challenges in data storage, power consumption, and tra...
Autonomous driving has emerged as a rapidly advancing field in both industry and academia over the past decade. Among the enabling technologies, computer vision (CV) has demonstrated high accuracy across various domains, making it a critical componen...
Decoding motor imagery (MI) of lower-limb movements from electroencephalography (EEG) signals remains a challenge due to the involvement of deep cortical regions, limiting the applicability of Brain–Computer Interfaces (BCIs). This study propos...
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...
This paper presents a method for recognizing sign language gestures corresponding to fruit names using electromyography (EMG) signals. The proposed system focuses on classification using a limited number of EMG channels, aiming to reduce classificati...
Face recognition technology utilizes unique facial features to analyze and compare individuals for identification and verification purposes. This technology is crucial for several reasons, such as improving security and authentication, effectively ve...
Stroke remains one of the leading causes of disability worldwide, often resulting in persistent impairments in gait and balance. Traditional rehabilitation methods—though beneficial—are limited by factors such as therapist dependency, low...
In this paper, we propose a novel visual tracking method with a object part-aware attention-based matching (OPAM) mechanism, which leverages local–global attention to enhance visual tracking performance. Our method introduces three key componen...
Bats are ecologically vital mammals, serving as pollinators, seed dispersers, and bioindicators of ecosystem health. Many species inhabit natural caves, which offer optimal conditions for survival but present challenges for direct ecological monitori...
In this article, the classification of signals arising from the movements of the lower limb of the leg (LLL) based on electromyography (EMG) (walking, sitting, up and down the stairs) was carried out. In the data collection process, 25 athletes aged...
Distributed target tracking in multi-agent networks plays a critical role in cooperative sensing and autonomous navigation. However, it faces significant challenges in highly dynamic and adversarial setups. This study aims to enhance the resilience o...
Electroencephalogram (EEG)-based identification offers a promising biometric solution by leveraging the uniqueness of individual brain activity patterns. This study proposes a framework based on a convolutional autoencoder (CAE) along with a traditio...
This study aims to compare decision tree and Analysis of Variance (ANOVA) techniques as feature selection methods, combined with Wavelet Packet Decomposition (WPD) for feature extraction, to enhance the diagnosis of faults in belt conveyor idlers. Be...
Rocket launches generate infrasound signatures that have been detected at great distances. Due to the sparsity of the networks that have made these detections, however, most signals are detected tens of minutes to hours after the rocket launch. In th...
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