Mostafa M. Fouda

• PhD (Information Sciences), Tohoku Univ., Japan
• Associate Professor at Idaho State University

The advanced metering infrastructure of the smart grid presents the biggest growth potential in the machine-to-machine market today. Spurred by recent advances in M2M technologies, SG smart meters are expected not to require human intervention in characterizing power requirements and energy distribution. However, there are many challenges in the de...

With the exponentially growing COVID-19 (coronavirus disease 2019) pandemic, clinicians continue to seek accurate and rapid diagnosis methods in addition to virus and antibody testing modalities. Because radiographs such as X-rays and computed tomography (CT) scans are cost-effective and widely available at public health facilities, hospital emerge...

In Beyond Fifth Generation (B5G) networks, Internet of Things (IoT) and massive Machine Type Communication (mMTC) traffic are anticipated to be offloaded by multi-hop, Device-to-Device (D2D)-enabled relay networks. The relays offer an energy and spectral-efficient solution to the rising problem of spectrum scarcity and overloading of cellular base...

In advanced metering infrastructure (AMI), smart meters (SMs), which are installed at the consumer side, send fine-grained power consumption readings periodically to the electricity utility for load monitoring and energy management. Change and transmit (CAT) is an efficient approach to collect these readings, where the readings are not transmitted...

In smart grid, malicious customers may compromise their smart meters (SMs) to report false readings to achieve financial gains illegally. Reporting false readings not only causes hefty financial losses to the utility but may also degrade the grid performance because the reported readings are used for energy management. This paper is the first work...

The rapid and low-power configuration capabilities of Reconfigurable Intelligent Surfaces (RISs) have made them an attractive option for future wireless networks in terms of energy efficiency. They have the ability to greatly increase connection and facilitate low-latency communications. However, because RIS-based systems often have a large number...

Future wireless networks could benefit from the energy-efficient, low-latency, and scalable deployments that Reconfigurable Intelligent Surfaces (RISs) offer. However, the creation of an effective low overhead channel estimate technique is a major obstacle in RIS-assisted systems, especially given the high number of RIS components and intrinsic har...

Background Obstructive sleep apnea (OSA) is a severe condition associated with numerous cardiovascular complications, including heart failure. The complex biological and morphological relationship between OSA and atherosclerotic cardiovascular disease (ASCVD) poses challenges in predicting adverse cardiovascular outcomes. While artificial intellige...

Adaptive game design is a dynamic gamification approach that changes game elements such as challenges, feed- back mechanisms, and rewards based on players’ preferences, behaviors, and needs. It is an emerging research field that aims to improve classic gamification techniques by adapting a game environment to meet the particular needs of various us...

The development of high-quality deep learning models demands the transfer of user data from edge devices, where it originates, to centralized servers. This central training approach has scalability limitations and poses privacy risks to private data. Federated Learning (FL) is a distributed training framework that empowers physical smart systems de...

Load forecasting (LF) is a crucial process of predicting future energy load and demand in smart grids, allowing for mitigating equipment failures and power outages, besides facilitating effective power dispatching and infrastructure planning. Methods used in LF range from traditional statistical and mathematical models to modern machine learning (M...

With the growing integration of IoT devices in critical infrastructure, cybersecurity threats such as Distributed Denial of Service (DDoS) attacks on Energy Hubs (EH) have become a significant concern. This study aims to address these challenges by evaluating the effectiveness of various supervised machine learning (ML) algorithms in predicting DDo...

Lung diseases such as COVID-19 and pneumonia can lead to breathing difficulties, decreased lung function, and respiratory failure, leading to death if not treated immediately. Chest X-ray imaging techniques are quick, effective, and inexpensive in controlling many of these diseases. Artificial intelligence has shown promising results in detecting m...

The fusion of blockchain and artificial intelligence (AI) marks a paradigm shift in healthcare, addressing critical challenges in securing electronic health records (EHRs), ensuring data privacy, and facilitating secure data transmission. This study provides a comprehensive analysis of the adoption of blockchain and AI within healthcare, spotlighti...

Pattern synthesis is widely used in many radar and communication systems and received great interest. So, this paper proposes a new beamforming strategy based on a hybrid combination between grey wolf optimizer (GWO) with L2-norm called proposed GWO. This approach is applied to synthesized uniform linear arrays (ULA), Chebyshav arrays, and shaped p...

Ensuring the durability of high-voltage (HV) cross-linked polyethylene (XLPE) cable insulation requires vigilant cleanliness maintenance during production to mitigate impurities, including oxidized parts and voids, which can compromise insulation integrity. Hence, this paper presents a MATLAB/Simulink partial discharge (PD) capacitive model of five...

Intrusion detection systems (IDS) play a critical role in ensuring the security and integrity of computer networks. There is a constant demand for the development of powerful, novel, and generalized methods for IDS that can accurately detect and classify intrusions. In this study, we aim to evaluate the benefits of linear classifiers (LC) and nonli...

5G technology has ushered in a new era of cellular networks characterized by unprecedented speeds and connectivity. However, these networks' dynamic and complex nature presents significant challenges in network management and Quality of Service (QoS) assurance. In this context, accurate throughput prediction is essential for optimizing network reso...

WiGig networks and 60 GHz frequency communications have a lot of potential for commercial and personal use. The high-frequency bands can provide high transmission rates, but their high amplitude makes it so the signal cannot go through any walls or obstacles. The signal also has a strong path loss element caused by the high frequency, significantly...

Background and novelty When RT-PCR is ineffective in early diagnosis and understanding of COVID-19 severity, Computed Tomography (CT) scans are needed for COVID diagnosis, especially in patients having high ground-glass opacities, consolidations, and crazy paving. Radiologists find the manual method for lesion detection in CT very challenging and t...

An earthquake early-warning system (EEWS) is an indispensable tool for mitigating loss of life caused by earthquakes. The ability to rapidly assess the severity of an earthquake is crucial for effectively managing earthquake disasters and implementing successful risk-reduction strategies. In this regard, the utilization of an Internet of Things (Io...

An innovative method to raise wireless communication systems’ efficiency is to use Reconfigurable Intelligent Surface (RIS). Unfortunately, determining the quantity and locations of the RIS elements continues to be difficult, requiring a clever optimization framework. Concerning the practical overlap between the related multi-RISs in wireless commu...

In the context of the growing proliferation of user devices and the concurrent surge in data volumes, the complexities arising from the substantial increase in data have posed formidable challenges to conventional machine learning model training. Particularly, this is evident within resource-constrained and security-sensitive environments such as t...

Background The field of precision medicine endeavors to transform the healthcare industry by advancing individualised strategies for diagnosis, treatment modalities, and predictive assessments. This is achieved by utilizing extensive multidimensional biological datasets encompassing diverse components, such as an individual's genetic makeup, functi...

Cardiovascular disease (CVD) diagnosis and treatment are challenging since symptoms appear late in the disease’s progression. Despite clinical risk scores, cardiac event prediction is inadequate, and many at-risk patients are not adequately categorised by conventional risk factors alone. Integrating genomic-based biomarkers (GBBM), specifically tho...

Knee Osteoarthritis (OA) is one of the most common joint diseases that may cause physical disability associated with a significant personal and socioeconomic burden. X-ray imaging is the cheapest and most common method to detect Knee (OA). Accurate classification of knee OA can help physicians manage treatment efficiently and slow knee OA progressi...

The adoption of IoT and monitoring devices in 5G and beyond networks has been widespread. Unmanned Aerial vehicles (UAVs) have shown success in connecting rural and remote areas due to the high cost of deploying infrastructures like cellular network base stations and optical fiber connections in vast landscapes with sparse populations. The constrai...

The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well carotid plaque features predict the likelihood of CAD and cardiovascular (CV) events using deep learning (DL) and compare against the machine learning (ML) paradigm. The...

As the Internet of Things (IoT) continues to expand its footprint across various sectors, including healthcare, industrial automation, and smart homes, the security of these interconnected devices becomes paramount. With the proliferation of IoT devices, the attack surface for potential cybersecurity threats has significantly increased, necessitati...

Due to the intricate relationship between the small non-coding ribonucleic acid (miRNA) sequences, the classification of miRNA species, namely Human, Gorilla, Rat, and Mouse is challenging. Previous methods are not robust and accurate. In this study, we present AtheroPoint’s GeneAI 3.0, a powerful, novel, and generalized method for extracting featu...

Background There are several antibiotic resistance genes (ARG) for the Escherichia coli (E. coli) bacteria that cause urinary tract infections (UTI), and it is therefore important to identify these ARG. Artificial Intelligence (AI) has been used previously in the field of gene expression data, but never adopted for the detection and classification...

This paper explores secret key generation in 5G and beyond LiFi networks using visible light in the downlink and infrared in the uplink. Unlike the existing works, we focus on a realistic indoor environment with multi-user mobility. Given inaccuracies in high-frequency channel models, we introduce the first deep learning model that combines the cha...

This paper provides a study of the latest target (object) detection algorithms for underwater wireless sensor networks (UWSNs). To ensure selection of the latest and state-of-the-art algorithms, only algorithms developed in the last seven years are taken into account that are not entirely addressed by the existing surveys. These algorithms are clas...

The Integrated Sensing and Communication (ISAC) system merged with Reconfigurable Intelligent Surface (RIS) has recently received much attention. This paper proposes an intelligent metaheuristic version of Enhanced Artificial Ecosystem Optimizer (EAEO) for a suggested beamforming optimization framework in ISAC systems with RIS. Two RIS are utilized...

In this paper, the problem of joint unmanned aerial vehicle (UAV) trajectory planning and low-orbit satellites (LEO-Sats) selection in space-air-ground integrated networks (SAGIN) will be investigated. This problem is of utmost importance when SAGIN is exploited for post-disaster relief services, where ground base stations (GBSs) within the post-di...

In this paper, we undertake an examination of the complicated challenges associated with bandwidth allocation and power control in multi- unmanned aerial vehicles (UAVs) network. The focal point of our investigation is the formulation and subsequent proposition of a novel algorithm aimed at optimizing bandwidth utilization and energy efficiency acr...

Malaria is a mosquito-borne, life-threatening, and contagious disease that has caused thousands of fatalities in recent years. Due to inadequate detection, the inexperience of laboratory personnel, and lack of advanced point-of-care equipment, the malaria-induced mortality rate is increasing. In addition to the traditional detection mechanisms, res...

In this paper, re-configurable intelligent reflecting surfaces (IRS) based on cell-free communications to serve multi-user (MU) are considered. This is to enhance the transmission for the next generation of wireless communications. This technique has witnessed lots of interest recently due to its ability to increase diversity gain, especially in th...

Employing RIS is an advanced strategy to enhance the efficiency of wireless communication systems. However, the number and positions of the RISs elements are still challenging and require a smart optimization framework. This paper aims to optimize the number of RISs subject to the technical limitations of the average achievable data rate with consi...

The continuous wireless coverage of high-speed trains (HSTs) constitutes a big challenge due to their incredible speed reaching hundreds of kilometers per hour (km/hr). This necessitates the deployment of massive number of ground base stations (BS), which is costly particularly in rural and wilderness areas. Likewise, satellites will not provide th...

Existing literature confirms the ability of machine learning to identify fraudulent smart grid power consumers who report false consumption readings to pay less electricity bills. Additionally, federated learning (FL) shows promise as a way to train the detection model without requiring data sharing, thereby safeguarding consumer privacy. However,...

With the proliferation of Beyond 5G (B5G) communication systems and heterogeneous networks, mobile broadband users are generating massive volumes of data that undergo fast processing and computing to obtain actionable insights. While analyzing this huge amount of data typically involves machine and deep learning-based data-driven Artificial Intelli...

Statistical tests-based approaches have been extensively researched for multiple antenna-based spectrum sensing (SS) in cognitive radio (CR). Nevertheless, their performance is neither satisfactory nor adequate to detect the primary user (PU) particularly in weak signal environments. In this paper, three novel statistical tests-based methods are de...

Earthquake early warning systems (EEWS) often rely on fast determination of earthquake source parameters, namely location, magnitude, and depth. In areas where the seismic network is coarse, the capability to determine source parameters based on data recorded by a single station is desirable. Moreover, being able to use a single component of the se...

Persistent automation of driving functions results in development of advanced driver assistance systems (ADAS) into fully autonomous driving systems. The environmental sensing capabilities of these systems have a significant impact on their performance, reliability, and safety. Accordingly, the automotive radar is an indispensable technology in the...

Due to the reliability and efficiency of keystroke dynamics, enterprises have adopted it widely in multi-factor authentication systems, effectively strengthening user authentication and thereby boosting the security of online and offline services. The existing works that detect imposter users suffer from performance and robustness degradation. Ther...

This paper studies the generation of cryptographic keys from wireless channels in light-fidelity (LiFi) networks. Unlike existing studies, we account for several practical considerations (a) realistic indoor multi-user mobility scenarios, (b) non-ideal channel reciprocity given the unique characteristics of the downlink visible light (VL) and uplin...

The 802.11 IEEE standard aims to update current Wireless Local Area Network (WLAN) standards to meet the high demands of future applications, such as 8K videos, augmented/virtual reality (AR/VR), the Internet of Things, telesurgery, and more. Two of the latest developments in WLAN technologies are IEEE 802.11be and 802.11ay, also known as Wi-Fi 7 a...

As vehicular communication networks embrace metaverse beyond 5G/6G systems, the rich content update via the least interfered subchannel of the optimal frequency band in a hybrid band vehicle to everything (V2X) setting emerges as a challenging optimization problem. We model this problem as a tradeoff between multi-band VR/AR devices attempting to p...

Background and Motivation: Coronary artery disease (CAD) has the highest mortality rate; therefore, its diagnosis is vital. Intravascular ultrasound (IVUS) is a high-resolution imaging solution that can image coronary arteries, but the diagnosis software via wall segmentation and quantification has been evolving. In this study, a deep learning (DL)...

Background and Motivation Lung computed tomography (CT) techniques have been utilized in the intensive care unit (ICU) for COVID-19 disease characterization due to its high-resolution imaging. Artificial Intelligence (AI) has significantly helped researchers in diagnosing COVID-19, and the proposed study hypothesized that the cloud-based explainabl...

Epilepsy is a prevalent neurological disorder characterized by recurrent seizures, affecting millions of people worldwide. Accurate and timely detection of epileptic seizures is crucial for patient management and treatment. Traditional seizure detection methods are often time-consuming and require expert interpretation, leading to a growing interes...