Khaled Elleithy

University of Bridgeport · Department of Computer Science & Engineering

In WSNs, the most critical issue is energy consumption as sensor nodes have limited resources. The sensors collect data from the environment where they can fail due to variations in pressure, temperature, and electromagnetic noise. All these can result in misleading readings and measurements where a lot of energy is consumed. Therefore, data fusion...

The applications of WSN can be quiet numerous. In applications like battlefield monitoring, grid power generation, health systems, sensors are deployed on large scale. During such deployment, energy efficiency must be proficient, which requires clustering, in the WSN architecture. Clustering architecture requires maintenance of sensor nodes due to...

The aim of this paper is to detect Rogue Access Points (RAPs) that clone legitimate Access Points (APs) characteristics. A novel passive approach that takes advantage of the characteristics of physical layer fields via the Radiotap length is proposed. This approach is a general fingerprint, thus, it can be used for different purposes such as identi...

the reported research in literature for message transformation by a third party does not provide the necessary efficiency and security against different attacks. The data transmitted through the computer network must be confidential and authenticated in advance. In this paper, we develop and improve security of the braided single stage quantum cryp...

Quantum machine learning holds the potential to revolutionize cancer treatment and diagnostic imaging by uncovering complex patterns beyond the reach of classical methods. This study explores the effectiveness of quantum convolutional layers in classifying ultrasound breast images for cancer detection. By encoding classical data into quantum states...

Current AI detection systems often struggle to distinguish between Arabic human-written text (HWT) and AI-generated text (AIGT) due to the small marks present above and below the Arabic text called diacritics. This study introduces robust Arabic text detection models using Transformer-based pre-trained models, specifically AraELECTRA, AraBERT, XLM-...

The effectiveness of existing AI detectors is notably hampered when processing Arabic texts. This study introduces a novel AI text classifier designed specifically for Arabic, tackling the distinct challenges inherent in processing this language. A particular focus is placed on accurately recognizing human-written texts (HWTs), an area where existi...

This research presents a novel approach to detecting epileptic seizures leveraging the strengths of Machine Learning (ML) and Deep Learning (DL) algorithms in EEG signals. Epileptic seizures are neurological events with distinctive features found in Electroencephalography (EEG) that lend considerable credibility to researchers. Machine Learning (ML...

Cybercriminals often use fraudulent emails and fictitious email accounts to deceive individuals into disclosing confidential information, a practice known as phishing. This study utilizes three distinct methodologies, Term Frequency-Inverse Document Frequency, Word2Vec, and Bidirectional Encoder Representations from Transformers, to evaluate the ef...

Quantum computing is a promising technology that may provide breakthrough solutions to today’s difficult problems such as breaking encryption and solving large-scale combinatorial optimization problems. An algorithm referred to as Quantum Approximate Optimization Algorithm (QAOA) has been recently proposed to approximately solve hard problems using...

Quantum Machine Learning (QML) is an interdisciplinary field combining Quantum Computing (QC) and Machine Learning (ML). It has gained increased attention due to advances in near-term hardware implementations of quantum devices. The use of QML has proven to result in a significant improvement in performance and computational speed. Consequently, QM...

Epileptic seizure detection classification distinguishes between epileptic and non-epileptic signals and is an important step that can aid doctors in diagnosing and treating epileptic seizures. In this paper, we studied the existing epileptic seizure detection methods in terms of challenges and processes developed based on electroencephalograph (EE...

In this paper, we present an overview of quantum neural network (QNN) and quantum computing benefits in the Artificial Intelligence field with methods used to enhance the application of machine learning. The approach uses quantum computers to enhance Convolutional Neural Network (CNN) with Hybrid QNNs using IBM Qiskit called the Convolutional Neura...

This study aims to examine information technology students' perceptions toward the use of virtual reality technology, their behavioral intention to use such technology for educational purposes, and the relationship between their perceptions toward the use of virtual reality technology and their behavioral intention to use virtual reality technology...

Clinical text classification of electronic medical records is a challenging task. Existing electronic records suffer from irrelevant text, misspellings, semantic ambiguity, and abbreviations. The approach reported in this paper elaborates on machine learning techniques to develop an intelligent framework for classification of the medical transcript...

This paper aims to design and implement a robust wireless charging system that utilizes affordable materials and the principle of piezoelectricity to generate clean energy to allow the user to store the energy for later use. A wireless charging system that utilizes the piezoelectricity generated as a power source and integrated with Qi-standard wir...

Face recognition is one of the most researched subjects in computer vision. The attention it receives is due to the complexity of the problem. Face recognition models have to deal with a wide variety of intraclass variations such as pose variations, facial expressions, the effect of aging, and natural occlusion due to different illumination. This c...

This paper introduces a novel approach to enhance the efficiency of compressing Arabic Unicode text using the Lempel-Ziv-Welch (LZW) technique. This method includes two stages: transformation and compression. During the first phase, a multi-level scheme that works according to the level of words, syllables, and characters replaces multi-byte symbol...

This paper addresses aspects related to quantum machine-based classification such as data encoding into quantum states, Barren plateau, robustness, and effectiveness with developing a classical artificial neural versus fully and hybrid quantum neural network approach. The two approaches were compared with a classical artificial neural network using...

The Wireless Sensor Networks (WSNs) are characterized by their widespread deployment due to low cost, but the WSNs are vulnerable to various types of attacks. To defend against the attacks, an effective security solution is required. However, the limits of these networks’ battery-based energy to the sensor are the most critical impediments to selec...

Shadows in images and videos can cause the failure of computer vision techniques’ performance, such as segmentation, tracking, object detection, and recognition. Therefore, we propose a unique shadow detection for images and videos using artificial intelligence techniques. Our system is effective and can process real-time frames with different text...

Recent rapid technological advancements in pattern recognition and computer vision have led to great results on a wide range of applications. One of these applications is herbal plant species identification, as the proper automated system for the recognition of herbal plants is required for botanists to study therapeutic and nutritional uses of her...

A high-efficiency crystalline silicon-based solar cell in the visible and near-infrared regions is introduced in this paper. A textured TiO2 layer grown on top of the active silicon layer and a back reflector with gratings are used to enhance the solar cell performance. The given structure is simulated using the finite difference time domain (FDTD)...

A low-cost Si-based optical nano-sensor that monitors traditional water pollutants is introduced in this paper. The introduced sensor works in the near-infrared region, 900 nm to 2500 nm spectral range. The proposed structure consists of a Si layer with an optimized thickness of 300 nm on the top of the Al layer acting as a back reflector. On the t...

Genres are one of the key features that categorize music based on specific series of patterns. However, the Arabic music content on the web is poorly defined into its genres, making the automatic classification of Arabic audio genres challenging. For this reason, in this research, our objective is first to construct a well-annotated dataset of five...

Machine and deep learning techniques are two branches of artificial intelligence that have proven very efficient in solving advanced human problems. The automotive industry is currently using this technology to support drivers with advanced driver assistance systems. These systems can assist various functions for proper driving and estimate drivers...

This work introduces a high-efficiency organic solar cell with grating nanostructure in both hole and electron transport layers and plasmonic gold nanoparticles (Au NPs) distributed on the zinc oxide (ZnO) layer. The periods of the grating structure in both hole and electro transport layers were optimized using Lumerical finite difference time doma...

Monitoring drivers’ emotions is the key aspect of designing advanced driver assistance systems (ADAS) in intelligent vehicles. To ensure safety and track the possibility of vehicles’ road accidents, emotional monitoring will play a key role in justifying the mental status of the driver while driving the vehicle. However, the pose variations, illumi...

Network optimization is a highly relevant solution to the growing demands of mobile communications. Increasing the efficiency of the existing spectrum and infrastructure drives down costs and improves provider networks' usability. This paper focuses on applying data mining to the evaluation of network performance as a viable tool for resource alloc...

According to the Center for Disease Control and Prevention (CDC), the average human life expectancy is 78.8 years. Specifically, 3.2 million deaths are reported yearly due to heart disease, cancer, Alzheimer’s disease, diabetes, and COVID-19. Diagnosing the disease is mandatory in the current way of living to avoid unfortunate deaths and maintain a...

Cardiovascular diseases have been reported to be the leading cause of mortality across the globe. Among such diseases, Myocardial Infarction (MI), also known as “heart attack”, is of main interest among researchers, as its early diagnosis can prevent life threatening cardiac conditions and potentially save human lives. Analyzing the Electrocardiogr...

Recent technology advances in CMOS image sensors (CIS) enable their utilization in the most demanding of surveillance fields, especially visual surveillance and intrusion detection in intelligent surveillance systems, aerial surveillance in war zones, Earth environmental surveillance by satellites in space monitoring, agricultural monitoring using...

Wireless sensor and actor networks (WSAN) is an area where sensors and actors collaborate to sense, handle and perform tasks in real-time. Thus, reliability is an important factor. Due to the natural of WSAN, actor nodes are open to failure. Failure of actor nodes degrades the network performance and may lead to network disjoint. Thus, fault tolera...

Electrocardiogram (ECG) gives essential information about different cardiac conditions of the human heart. Its analysis has been the main objective among the research community to detect and prevent life threatening cardiac circumstances. Traditional signal processing methods, machine learning and its subbranches, such as deep learning, are popular...

With the introduction of the Convolutional Neural Network (CNN) and other classical algorithms, facial and object recognition have made significant progress. However, in a situation where there are few label examples or the environment is not ideal, such as lighting conditions, orientations, and so on, performance is disappointing. Various methods,...

Android receives major attention from security practitioners and researchers due to the influx number of malicious applications. For the past twelve years, Android malicious applications have been grouped into families. In the research community, detecting new malware families is a challenge. As we investigate, most of the literature reviews focus...

The vehicular ad hoc network (VANET) is a method through which Intelligent Transportation Systems (ITS) have become important for the benefit of daily life. Real-time detection of all forms of attacks, including hybrid DoS attacks in IEEE 802.11p, has become an urgent issue for VANET. This is due to sporadic real-time exchange of safety and road em...

The vehicular ad hoc network (VANET) is a method through which Intelligent Transportation Systems (ITS) have become important for the benefit of daily life. Real-time detection of all forms of attacks, including hybrid DoS attacks in IEEE 802.11p, has become an urgent issue for VANET. This is due to sporadic real-time exchange of safety and road em...

Internet of things has become integrated in all aspects of life. Data and devices are interconnected to provide fast, efficient, and low-cost services. Radio Frequency Identification (RFID) is a wireless sensor network technology that is implemented with the Internet of Things (IoT) in many fields such as inventory management, product identificatio...

VANET (vehicular ad hoc network) has a main objective to improve driver safety and traffic efficiency. The intermittent exchange of real-time safety message delivery in VANET has become an urgent concern due to DoS (denial of service) and smart and normal intrusions (SNI) attacks. The intermittent communication of VANET generates huge amount of dat...

VANET (vehicular ad hoc network) has a main objective to improve driver safety and traffic efficiency. The intermittent exchange of real-time safety message delivery in VANET has become an urgent concern due to DoS (denial of service) and smart and normal intrusions (SNI) attacks. The intermittent communication of VANET generates huge amount of dat...

As more devices become internet-connected, there is a greater need for secure and discrete device-to-device communication. Data shows that at the time of this writing the number of internet-connected devices is around 20 billion and is expected to increase to 29 billion by the end of 2022. In the early days of IoT the majority of the market was com...

Wireless sensor and actor networks (WSAN) is an area where sensors and actors collaborate to sense, handle and perform tasks in real-time. Thus, reliability is an important factor. Due to the natural of WSAN, actor nodes are open to failure. Failure of actor nodes degrades the network performance and may lead to network disjoint. Thus, fault tolera...

Due to recent developments in hardware and software technologies for mobile phones, people depend on their smartphones more than ever before. Today, people conduct a variety of business, health, and financial transactions on their mobile devices. This trend has caused an influx of mobile applications that require users’ sensitive information. As th...

Modern wireless sensor networks have adopted the IEEE 802.15.4 standard. This standard defines the first two layers, the physical and medium access control layers; determines the radio wave used for communication; and defines the 128-bit advanced encryption standard (AES-128) for encrypting and validating the transmitted data. However, the standard...

p class="Abstract"> A directed graph represents an accurate picture of course descriptions for online courses through computer-based implementation of various educational systems. E-learning and m-learning systems are modeled as a weighted, directed graph where each node represents a course unit. The Learning Path Graph (LPG) represents and describ...

Despite the popularity of wireless sensor networks (WSNs) in a wide range of applications, security problems associated with them have not been completely resolved. Middleware is generally introduced as an intermediate layer between WSNs and the end user to resolve some limitations, but most of the existing middleware is unable to protect data from...

Eye exam can be as efficacious as physical one in determining health concerns. Retina screening can be the very first clue to detecting a variety of hidden health issues including pre-diabetes and diabetes. Through the process of clinical diagnosis and prognosis; ophthalmologists rely heavily on the binary segmented version of retina fundus image;...

Optic disc segmentation in retinal fundus images plays a critical rule in diagnosing a variety of pathologies and abnormalities related to eye retina. Most of the abnormalities that are related to optic disc lead to structural changes in the inner and outer zones of optic disc. Optic disc segmentation on the level of whole retina image degrades the...

Our research currently focusing on image sensors predominantly the sensors implemented using CMOS (Complementary Metal Oxide Semiconductor) technology. These sensors designated as CMOS sensors which were introduced after CCD (Charge-coupled Devices) sensors since CCDs having some drawbacks in terms of its power and making cost compared to CMOS sens...

Wireless Sensor and Actor Networks (WSAN) is an area where sensors and actors collaborate to sense, handle and perform tasks in real-time. Thus, reliability is an important factor. Due to the natural of WSAN, actor nodes are variable to failure. Failure of actor nodes degrades the network performance and may leads to network disjoint. Thus, Fault t...

Wireless sensor networks (WSNs) are deployed in many applications such as those used in monitoring, by the military, in healthcare, etc. Since these applications deal with the transfer of sensitive data, they need protection from various attacks and intrusions. From the current literature, we observed that existing security algorithms are not suita...

Despite the popularity of wireless sensor networks (WSNs) in a wide range of applications, security problems associated with them have not been completely resolved. Middleware is generally introduced as an intermediate layer between WSNs and the end user to resolve some limitations, but most of the existing middleware is unable to protect data from...