Hamila Ridha

Qatar University · Department of Electrical Engineering

The success of modern deep learning is attributed to two key elements: huge amounts of training data and large model sizes. Where a vast amount of data allows the model to learn more features, the large model architecture boosts the learning capability of the model. However, both these factors result in prolonged training time. In some practical ap...

The advent of Intelligent Reflecting Surfaces (IRS) and Unmanned Aerial Vehicles (UAVs) is setting a new benchmark in the field of wireless communications. IRS, with their groundbreaking ability to manipulate electromagnetic waves, have opened avenues for substantial enhancements in signal quality, network efficiency, and spectral usage. These surf...

The traditional healthcare system is increasingly challenged by its dependence on in-person consultations and manual monitoring, struggling with issues of scalability, the immediacy of care, and efficient resource allocation. As the global population ages and chronic conditions proliferate, the demand for healthcare systems capable of delivering ef...

Visual crowd counting estimates the density of the crowd using deep learning models such as convolution neural networks (CNNs). The performance of the model heavily relies on the quality of the training data that constitutes crowd images. In harsh weather such as fog, dust, and low light conditions, the inference performance may severely degrade on...

Over the last decade, there has been a remarkable surge in interest in automated crowd monitoring within the computer vision community. Modern deep‐learning approaches have made it possible to develop fully automated vision‐based crowd‐monitoring applications. However, despite the magnitude of the issue at hand, the significant technological advanc...

Crowdsourced live streaming services (CLS) present significant challenges due to massive data size and dynamic user behavior. Service providers must accommodate personalized QoE requests, while managing computational burdens on edge servers. Existing CLS approaches use a single edge server for both transcoding and user service, potentially overwhel...

Automatic crowd counting using density estimation has gained significant attention in computer vision research. As a result, a large number of crowd counting and density estimation models using convolution neural networks (CNN) have been published in the last few years. These models have achieved good accuracy over benchmark datasets. However, atte...

Wireless communication is one of the most substantial types of communication nowadays, leading to the IoT revolution and increasing demand for IoT networks. On the other hand, this demand also leads to an increase in the number of resource-constrained devices, which creates a new problem related to vulnerabilities to attacks. The handling of attack...

Automatic crowd counting using density estimation has gained significant attention in computer vision research. As a result, a large number of crowd counting and density estimation models using convolution neural networks (CNN) have been published in the last few years. These models have achieved good accuracy over benchmark datasets. However, atte...

Data centers serve as the backbone for cloud computing, enterprise services, and infrastructure-based offerings. One area of ongoing research in data center networking focuses on innovating new topologies for large-scale node connectivity. These topologies must incorporate fault-tolerant and efficient routing algorithms. Consequently, the data cent...

The rapid outbreak of COVID-19 pandemic invoked scientists and researchers to prepare the world for future disasters. During the pandemic, global authorities on healthcare urged the importance of disinfection of objects and surfaces. To implement efficient and safe disinfection services during the pandemic, robots have been utilized for indoor asse...

Density estimation is one of the most widely used methods for crowd counting in which a deep learning model learns from head-annotated crowd images to estimate crowd density in unseen images. Typically, the learning performance of the model is highly impacted by the accuracy of the annotations and inaccurate annotations may lead to localization and...

Deep learning models require an enormous amount of data for training. However, recently there is a shift in machine learning from model-centric to data-centric approaches. In data-centric approaches, the focus is to refine and improve the quality of the data to improve the learning performance of the models rather than redesigning model architectur...

Video surveillance using drones is both convenient and efficient due to the ease of deployment and unobstructed movement of drones in many scenarios. An interesting application of drone-based video surveillance is to estimate crowd densities (both pedestrians and vehicles) in public places. Deep learning using convolution neural networks (CNNs) is...

Crowd counting is an effective tool for situational awareness in public places. Automated crowd counting using images and videos is an interesting yet challenging problem that has gained significant attention in computer vision. Over the past few years, various deep learning methods have been developed to achieve state-of-the-art performance. The m...

5G communication brings substantial improvements in the quality of service provided to various applications by achieving higher throughput and lower latency. However, interactive multimedia applications (e.g., ultra high definition video conferencing, 3D and multiview video streaming, crowd-sourced video streaming, cloud gaming, virtual and augment...

Device mobility in dense Wi-Fi networks offers several challenges. Two well-known problems related to device mobility are handover prediction and access point selection. Due to the complex nature of the radio environment, analytical models may not characterize the wireless channel, which makes the solution of these problems very difficult. Recently...

Myocardial infarction (MI) is a life-threatening disorder that occurs due to a prolonged limitation of blood supply to the heart muscles, and which requires an immediate diagnosis to prevent death. To detect MI, cardiologists utilize in particular echocardiography, which is a non-invasive cardiac imaging that generates real-time visualization of th...

Advances in communication technologies and computational capabilities of Internet of Things (IoT) devices enable a range of complex applications that require ever increasing processing of sensors' data. An illustrative example is real-time video surveillance that captures videos of target scenes and process them to detect anomalies using deep learn...

5G communication brings substantial improvements in the quality of service provided to various applications by achieving higher throughput and lower latency. However, interactive multimedia applications (e.g., ultra high definition video conferencing, 3D and multiview video streaming, crowd-sourced video streaming, cloud gaming, virtual and augment...

Video traffic over the Internet is increasing rapidly, reaching up to 82% of the total Internet traffic by 2022. This enormous growth of video traffic which also include immersive video content (augmented reality and virtual reality streaming) is challenging for the existing network architectures. Mobile edge computing (MEC) is arising as a promisi...

Device mobility in dense Wi-Fi networks offers several challenges. Two well-known problems related to device mobility are handover prediction and access point selection. Due to the complex nature of the radio environment, analytical models may not characterize the wireless channel, which makes the solution of these problems very difficult. Recently...

The Coronavirus disease 2019 (COVID-19) outbreak continues to significantly expose the vulnerabilities of healthcare systems around the world. These unprecedented circumstances create an opportunity for improving healthcare services which is desperately needed. This paper proposes a novel framework that distributes the patients across heterogeneous...

The usage of unmanned aerial vehicles (UAVs) in civil and military applications continues to increase due to the numerous advantages that they provide over conventional approaches. Despite the abundance of such advantages, it is imperative to investigate the performance of UAV utilization while considering their design limitations. This paper inves...

Background : COVID-19 is a pandemic that had already infected more than forty-six million people and caused more than a million deaths by 1 st of November 2020. The virus pandemic appears to have had a catastrophic effect on the global population's safety. Therefore, efficient detection of infected patients is a key phase in the battle against COVI...

Investigating the physical layer security performance of full-duplex (FD) radio transceivers has been the subject of numerous research studies. However, self-interference cancellation that enables full exploitation of FD communications is a crucial aspect that deserves special attention. Hence, in this paper, we analyze the effect of a FD transceiv...

Big data enables the optimization of complex supply chains through Machine Learning (ML)-based data analytics. However, data analytics comes with challenges such as the loss of control and privacy leading to increased risk of data breaches. Federated Learning (FL) is an approach in the ML arena that promises privacy-preserving and distributed model...

Cardiac imaging known as echocardiography is a non-invasive tool utilized to produce data including images and videos, which cardiologists use to diagnose cardiac abnormalities in general and myocardial infarction (MI) in particular. Echocardiography machines can deliver abundant amounts of data that need to be quickly analyzed by cardiologists to...

Myocardial infarction (MI), or commonly known as heart attack, is a life-threatening health problem worldwide from which 32.4 million people suffer each year. Early diagnosis and treatment of MI are crucial to prevent further heart tissue damages or death. The earliest and most reliable sign of ischemia is regional wall motion abnormality (RWMA) of...

Internet of Things (IoT) environments are widely employed in industrial applications including intelligent transportation systems, healthcare systems, and building energy management systems. For such environments of highly sensitive data, adapting scalable and flexible communication with efficient security is vital. Research investigated wireless A...

The Industrial Internet of Things (IIoT) has become very popular in recent years. However, IIoT is still an attractive and vulnerable target for attackers to exploit and experiment with different types of attacks. To confront this problem, the research community began exploring novel systems to protect the network. However, there are concerns relat...

Ramp metering is typically proposed as a responsive strategy that takes freeway traffic parameters as control inputs to the ramp control logic. Such a strategy can be implemented in two ways; isolated ramp control or coordinated ramp control. Coordinated ramp control typically involves the cooperation between several ramp meters connected to a free...

Ramp metering is typically proposed as a responsive strategy that takes freeway traffic parameters as control inputs to the ramp control logic. Such a strategy can be implemented in two ways; isolated ramp control or coordinated ramp control. Coordinated ramp control typically involves the cooperation between several ramp meters connected to a free...

This paper proposes a secure orthogonal frequency division multiplexing (OFDM) waveform based on two physical-layer secrecy enhancing methods. The first method is time-domain pre-coding that involves interleaving and scaling based on a key shared between two legitimate parties adopting the OFDM waveform. The second method is a random change of the...

Myocardial infarction (MI), or commonly known as heart attack, is a life-threatening worldwide health problem from which 32.4 million of people suffer each year. Early diagnosis and treatment of MI are crucial to prevent further heart tissue damages. However, MI detection in early stages is challenging because the symptoms are not easy to distingui...

Recently, machine learning algorithms have been proposed to design new security systems for anomalies detection as they exhibit fast processing with real-time predictions. However, one of the major challenges in machine learning-based intrusion detection methods is how to include enough training examples for all the possible classes in the model to...

Echocardiogram (echo) is the earliest and the primary tool for identifying regional wall motion abnormalities (RWMA) in order to diagnose myocardial infarction (MI) or commonly known as heart attack. This paper proposes a novel approach, Active Polynomials, which can accurately and robustly estimate the global motion of the Left Ventricular (LV) wa...

The growth of cloud-based services is mainly supported by the core networking infrastructures of large-scale data centers, while the scalability of these services is influenced by the performance and dependability characteristics of data centers. Hence, the data center network must be agile and reconfigurable in order to respond quickly to the ever...

Machine learning techniques are becoming mainstream in intrusion detection systems as they allow realtime response and have the ability to learn and adapt. By using a comprehensive dataset with multiple attack types, a well-trained model can be created to improve the anomaly detection performance. However, high dimensional data present a significan...

A major performance limiter in amplify-and-forward (AF) full-duplex (FD) relaying is the high level of residual self-interference (SI) due to the imperfect estimation of the effective self-interfering channel. One primary obstacle that contributes to the ineffectiveness of estimating the effective SI channel is the transceiver's radio-frequency (RF...

The heart sound signals (Phonocardiogram - PCG) enable the earliest monitoring to detect a potential cardiovascular pathology and have recently become a crucial tool as a diagnostic test in outpatient monitoring to assess heart hemodynamic status. The need for an automated and accurate anomaly detection method for PCG has thus become imminent. To d...

This paper addresses the evaluation of the performance of a full-duplex (FD) jammer and intercepting node, where the FD node attempts to disrupt the communication link of an intruding unmanned aerial vehicle (UAV). The FD node’s performance is evaluated by deriving an analytical expression of the probability of successfully interrupting the communi...

Internet of Things (IoT) networks operating in lightweight resource-constrained devices have been growing constantly in a wide range of areas. Such networks collect sensitive information over time that represent the users' behavioral patterns, which necessitates the need of safe data communication. IoT distributed systems are incurred with cyber-se...

With the growing need of developing real-time energy management and automation systems, building energy efficiency is of large focus in recent research. In particular, school buildings require special attention to occupants’ comfort and behavioral patterns related to the power consumed by heavy functional electrical systems. This paper introduces a...

Ramp metering is an effective way of maintaining optimum traffic conditions and mitigating congestion on freeways. Several strategies for ramp metering exist in the literature. They are typically based on the freeway traffic parameters as control inputs to the ramp control logic. The ramp signal can be controlled in two ways, i.e., locally controll...

Echocardiogram (echo) is the earliest and the primary tool for identifying regional wall motion abnormalities (RWMA) in order to diagnose myocardial infarction (MI) or commonly known as heart attack. This paper proposes a novel approach, Active Polynomials, which can accurately and robustly estimate the global motion of the Left Ventricular (LV) wa...

Wi-Fi Direct enables direct communication between Wi-Fi devices by forming Peer to Peer (P2P) groups. In each P2P group, one device becomes the Group Owner (GO) and serves as an access point (AP) to connect the remaining devices. The group formation in Wi-Fi Direct has two major limitations. Firstly, it is initiated between two P2P devices only. It...

Wi-Fi as a wireless networking technology has become a widely acceptable commonplace. Over the course of time, the applications landscape of Wi-Fi networks is growing tremendously. The proliferation of new services is driving the industry to adopt novel and agile approaches to ensure the quality of experience delivered to the end user. To enhance e...

The dual active full bridge (DAFB) is one of the promising isolated DC/DC converter topologies that will play a significant role in the future of electric vehicle (EV) integration in smart grids (SGs). This is due to its inherent soft switching and control simplicity. Therefore, this study presents first the latest developments related to the desig...

The smart grid (SG) modernizes the aging power grid by using two-way reliable communications dedicated to adaptive energy management. To achieve this goal, smart utility networks (SUNs) are used to efficiently connect the SG devices. However, the SUNs are designed to work on unlicensed frequency bands and are very sensitive to interferences from ot...

In this paper, we investigate the tradeoff between security and throughput and between security and queuing delay in wiretap time-division multiple access (TDMA) networks. We derive a simple relationship, characterized by a single key system parameter, between the stable-throughput region, where there are no perfect secrecy constraints on the data...