Ibrahim M. Elfadel
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View article: Advances in machine and deep learning for ECG beat classification: a systematic review
Advances in machine and deep learning for ECG beat classification: a systematic review Open
The electrocardiogram (ECG) is an important tool for exploring the structure and function of the heart due to its low cost, ease of use, efficiency, and non-invasive nature. With the rapid development of artificial intelligence (AI) in the…
View article: Multi-datasets transfer multitask learning for simultaneous blood glucose and blood pressure monitoring using common PPG features
Multi-datasets transfer multitask learning for simultaneous blood glucose and blood pressure monitoring using common PPG features Open
The simultaneous monitoring of both blood glucose level (BGL) and blood pressure (BP) has rarely been studied directly. The exploitation of physiological interactions between them will advance the learning of either task. However, the lack…
View article: Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors
Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors Open
Depression presents a significant challenge to global mental health, often intertwined with factors including oxidative stress. Although the precise relationship with mitochondrial pathways remains elusive, recent advances in machine learn…
View article: Residual Speech Embeddings for Tone Classification: Removing Linguistic Content to Enhance Paralinguistic Analysis
Residual Speech Embeddings for Tone Classification: Removing Linguistic Content to Enhance Paralinguistic Analysis Open
Self-supervised learning models for speech processing, such as wav2vec2, HuBERT, WavLM, and Whisper, generate embeddings that capture both linguistic and paralinguistic information, making it challenging to analyze tone independently of sp…
View article: A Low-Complexity Combined Encoder-LSTM-Attention Networks for EEG-based Depression Detection
A Low-Complexity Combined Encoder-LSTM-Attention Networks for EEG-based Depression Detection Open
Despite the high performance of existing state-of-the-art deep learning models for depression detection using electroencephalography (EEG), they incur a heavy computational burden. In this paper, we propose an efficient model consisting of…
View article: Proactive Random-Forest Autoscaler for Microservice Resource Allocation
Proactive Random-Forest Autoscaler for Microservice Resource Allocation Open
Cloud service providers have been shifting their workloads to microservices to take advantage of their modularity, flexibility, agility, and scalability. However, numerous obstacles remain to achieving the most out of microservice deployme…
View article: Learning Without Forgetting: A New Framework for Network Cyber Security Threat Detection
Learning Without Forgetting: A New Framework for Network Cyber Security Threat Detection Open
Progressive learning addresses the problem of incrementally learning new tasks without compromising the prediction accuracy of previously learned tasks. In the context of artificial neural networks, several algorithms exist for achieving t…
View article: Lightweight, Single-Clock-Cycle, Multilayer Cipher for Single-Channel IoT Communication: Design and Implementation
Lightweight, Single-Clock-Cycle, Multilayer Cipher for Single-Channel IoT Communication: Design and Implementation Open
The area of lightweight cryptography for constrained nodes has been quite well researched since the advent of RFID tags. However, the important issue of the integrated design of a secure, ultra-low power, small-footprint IoT transceiver ha…
View article: Cryptomining Detection in Container Clouds Using System Calls and Explainable Machine Learning
Cryptomining Detection in Container Clouds Using System Calls and Explainable Machine Learning Open
The use of containers in cloud computing has been steadily increasing.With the emergence of Kubernetes, the management of applications inside containers (or pods) is simplified.Kubernetes allows automated actions like self-healing, scaling…
View article: Shoe-Integrated, Force Sensor Design for Continuous Body Weight Monitoring
Shoe-Integrated, Force Sensor Design for Continuous Body Weight Monitoring Open
Traditional pedobarography methods use direct force sensor placement in the shoe insole to record pressure patterns. One problem with such methods is that they tap only a few points on the flat sole under the foot and, therefore, do not ac…
View article: BioCNN: A Hardware Inference Engine for EEG-Based Emotion Detection
BioCNN: A Hardware Inference Engine for EEG-Based Emotion Detection Open
EEG-based emotion classifiers have the potential of significantly improving the social integration of patients suffering from neurological disorders such as Amyotrophic Lateral Sclerosis or the acute stages of Alzheimer's disease. Emotion …
View article: MEMS Accelerometers
MEMS Accelerometers Open
Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact f…
View article: Editorial for the Special Issue on MEMS Accelerometers
Editorial for the Special Issue on MEMS Accelerometers Open
Micro-Electro-Mechanical Systems (MEMS) devices are widely used for motion, pressure, light, and ultrasound sensing applications [...]
View article: Monolithic Multi Degree of Freedom (MDoF) Capacitive MEMS Accelerometers
Monolithic Multi Degree of Freedom (MDoF) Capacitive MEMS Accelerometers Open
With the continuous advancements in microelectromechanical systems (MEMS) fabrication technology, inertial sensors like accelerometers and gyroscopes can be designed and manufactured with smaller footprint and lower power consumption. In t…
View article: Large-Scale 3D Chips: Challenges and Solutions for Design Automation, Testing, and Trustworthy Integration
Large-Scale 3D Chips: Challenges and Solutions for Design Automation, Testing, and Trustworthy Integration Open
Three-dimensional (3D) integration of electronic chips has been advocated by both industry and academia for many years. It is acknowledged as one of the most promising approaches to meet ever-increasing demands on performance, functionalit…
View article: Power management of pulsed-index communication protocols
Power management of pulsed-index communication protocols Open
Pulsed-Index Communication (PIC) is a novel technique for single-channel, high-data-rate, low-power dynamic signaling that does not require any clock and data recovery (CDR). It is fully adapted to the simple yet robust communication needs…