S. Harous

• PhD
• Professor (Full) at University of Sharjah

Combining metaheuristics with exact methods improves solution quality by efficiently exploring promising regions and refining the obtained solutions. This paper introduces a novel hybrid approach that combines exact methods and metaheuristics to address the Traveling Tournament Problem (TTP) in sports scheduling. The TTP, a critical aspect of sport...

In recent years, the concept of the metaverse has gained considerable momentum as virtual environments become more immersive and sophisticated. As this technology advances, it can potentially affect various aspects of our lives, including how we produce, consume, and trade energy. Peer-to-peer (P2P) energy trading, facilitated by digital twins (DTs...

Chaos theory, with its unique blend of randomness and ergodicity, has become a powerful tool for enhancing metaheuristic algorithms. In recent years, there has been a growing number of chaos-enhanced metaheuristic algorithms (CMAs), accompanied by a notable scarcity of studies that analyze and organize this field. To respond to this challenge, this...

This work presents a systematic mapping study on Sybil attack management in wireless ad hoc networks (WANETs). Sybil attacks pose significant threats to the security and performance of WANETs because they allow malicious nodes to claim multiple identities illegitimately. To address this issue, we conducted a comprehensive review of research from 20...

The increased emphasis on clean energy has accelerated the integration of renewable energy sources into electrical grids, resulting in the rise of peer-to-peer energy trading systems. For optimal power dispatch and management the Energy Internet concept advocates using energy routers. Efficient energy routing algorithms are crucial for successful e...

Intelligent Transportation Systems (ITS) generate massive amounts of Big Data through both sensory and non-sensory platforms. The data support batch processing as well as stream processing, which are essential for reliable operations on the roads and connected vehicles in ITS. Despite the immense potential of Big Data intelligence in ITS, autonomou...

Viewer engagement in videos has consistently low due to excessive advertisements during or before playback, long startup delays, pauses, blurring, poor resolution, and repetitive, intrusive ads. Although many well-established algorithms and techniques claim to improve user engagement, there is no universal solution that addresses all user needs and...

This study conducts a comparative analysis of the performance of ten novel and well-performing metaheuristic algorithms for parameter estimation of solar photovoltaic models. This optimization problem involves accurately identifying parameters that reflect the complex and nonlinear behaviours of photovoltaic cells affected by changing environmental...

Deep Reinforcement Learning (DRL) has become a fundamental element in advancing Autonomous Systems, significantly transforming fields like autonomous vehicles, robotics, and drones. This survey paper provides a comprehensive overview of the role of DRL in autonomous systems, focusing on recent advancements, applications, and challenges. Through a s...

The IoT has interconnected devices that collaborate via the Internet. Yet, its widespread connectivity and data generation pose cybersecurity risks. Integrating robust intrusion detection systems (IDSs) into the architecture has become crucial. IDSs safeguard data, detect attacks, and ensure network security and privacy. Constructing anomaly-based...

Volumetric video streaming technologies are the future of immersive media services such as virtual, augmented, and mixed-reality experiences. The challenges surrounding such technologies are tremendous due to the high network bandwidth needed to produce high-quality and low-latency streams. Many techniques and solutions have been proposed across th...

Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization problems. This approach aims to leverage the strengths of multiple algorithms, enhancing solution quality, convergence speed, and robustness, thereby offering a more versatile and effi...

Machine learning (ML) represents one of the main pillars of the current digital era, specifically in modern real-world applications. The Internet of Things (IoT) technology is foundational in developing advanced intelligent systems. The convergence of ML and IoT drives significant advancements across various domains, such as making IoT-based securi...

The capability to accurately detect web application attacks, especially in a timely fashion, is crucial but remains an ongoing challenge. This study provides an in-depth evaluation of 19 traditional machine learning techniques for detecting web application attacks. The evaluation was conducted across three distinct experiments on refined datasets d...

Integrating physical processes with computational components creates cyber‐physical systems (CPS) that seamlessly interact between the physical and digital worlds. The cyber‐physical system has become an interesting research area and an attractive application domain, especially in industry based on the big advantages of this new paradigm. All compa...

The growing depletion of fossil fuels has led to the use of distributed renewable energy sources. This shift has altered the grid structure from centralized to distributed, where energy flows from multiple sources through multiple paths, besides producing a more competitive and dynamic energy market, posing new problems to power system management....

Clustering is one of the most important approaches used to extend the lifetime of Wireless Sensor Networks (WSN). The fundamental metric taken by clustering algorithms is energy enhancement. Moreover, network coverage and load balance are two important approaches that play crucial roles in improving network lifetime and delivery since the former fo...

This study introduces an FER-based machine learning framework for real-time QoE assessment in video streaming. This study’s aim is to address the challenges posed by end-to-end encryption and video advertisement while enhancing user QoE. Our proposed framework significantly outperforms the base reference, ITU-T P.1203, by up to 37.1% in terms of ac...

Wireless body area networks (WBANs) have emerged as a promising solution for addressing challenges faced by elderly individuals, limited medical facilities, and various chronic medical conditions. WBANs consist of wearable sensing and computing devices interconnected through wireless communication channels, enabling the collection and transmission...

Emojis have become a crucial part of text-based communication in recent years, especially on social media and messaging services. As a result, emoji prediction has gained increasing attention as a research topic in Natural Language Processing. Emoji recommendation is a task of predicting relevant emojis based on the emotional and contextual orienta...

With end-to-end encryption for video streaming services becoming more popular, network administrators face new challenges in preserving network performance and user experience. Video ads may cause traffic congestion and poor Quality of Experience. Because of the natural variation in user interests and network situations, traditional algorithms for...

Web applications remain a significant attack vector for cybercriminals seeking to exploit application vulnerabilities and gain unauthorized access to privileged data. In this research, we evaluate the efficacy of eight supervised machine learning algorithms - Naive Bayes, Decision Tree, AdaBoost, Random Forest, Logistic Regression, K-Nearest Neighb...

The feature selection problem involves selecting a subset of relevant features to enhance the performance of machine learning models, crucial for achieving model accuracy. Its complexity arises from the vast search space, necessitating the application of metaheuristic methods to efficiently identify optimal feature subsets. In this work, we employe...

Delivering real-time multimedia content for safety applications over vehicular networks presents significant challenges due to rapidly changing network topology, high node mobility, and fluctuating traffic demands, compounded by substantial data volumes and network resource limitations. This paper proposes the Multi-Path Transmission Protocol for V...

Presents corrections to the paper, An Opposition-Based Great Wall Construction Metaheuristic Algorithm With Gaussian Mutation for Feature Selection.

Energy routing stands out as one of the most critical challenges within energy networks. Path selection, a fundamental aspect of energy routing, poses a complex problem aimed at identifying the route with minimal power loss. Numerous studies have been conducted to solve this issue. Some of these approaches are bio-inspired, while the rest are graph...

Technological advancements in electronics and power generation devices have led to the development of smart grids and the energy internet. Energy routing is a critical step in creating a reliable and functional energy system capable of harnessing the full potential of renewable energy. One of the major challenges in energy routing is the optimal pa...

Advances in technology in education have had a profound impact on Human-Computer Interaction. In this article, we explore how emerging technologies can make learning more affordable and accessible. This study aims to present a new approach to ubiquitous learning, which uses a multi-agent system to facilitate the learning process. To develop the mul...

Ensuring IoT security is of utmost importance in today’s interconnected world. IoT devices are prone to various security threats and vulnerabilities, making it essential to im- plement robust security measures. Intrusion detection plays an instrumental role in safeguarding network information security. However, traditional machine learning techniqu...

In this paper, we propose a novel methodology that combines the opposition Nelder–Mead algorithm and the selection phase of the genetic algorithm. This integration aims to enhance the performance of the overall algorithm. To evaluate the effectiveness of our methodology, we conducted a comprehensive comparative study involving 11 state-of-the-art a...

Misdiagnosis is a critical issue in healthcare, which can lead to severe consequences for patients, including delayed or inappropriate treatment, unnecessary procedures, psychological distress, financial burden, and legal implications. To mitigate this issue, we propose using deep learning algorithms to improve diagnostic accuracy. However, buildin...

Users’ security is one of the most important issues in Internet of Things (IoT) due to the high number of IoT devices involved in different applications. Security threats are evolving at a rapid pace that make the current security and privacy measures unsuitable. Therefore, several researchers have been attracted by this domain with the aim of prop...

This paper presents a comprehensive systematic review of personalized learning software systems. All the systems under review are designed to aid educational stakeholders by personalizing one or more facets of the learning process. This is achieved by exploring and analyzing the common architectural attributes among personalized learning software s...

Advances in technology in education have had a profound impact on Human Computer Interaction. The ubiquity of computer technology means that ubiquitous learning (U-learning) has really arrived on the scene. In this article, we explore how emerging technologies can make learning more affordable and accessible. Our aim is to present a new approach to...

Misdiagnosis is a critical issue in healthcare, which can lead to severe consequences for patients, in- cluding delayed or inappropriate treatment, unneces- sary procedures, psychological distress, financial bur- den, and legal implications. To mitigate this issue, we propose using deep learning algorithms to improve diag- nostic accuracy. However,...

The present work strives to investigate the effect of using dimensionality reduction techniques (DRTs) on breast cancer (BC) classification problem. Primarily, we focused on the following five (DRTs): Auto-Encoders (AE), T-Distributed Stochastic Neighbor Embedding (T- SNE), Recursive Feature Elimination (RFE), Isometric Feature Mapping (Isomap), an...

AADL—architecture analysis and design language—has proven to be important in developing real‐time embedded systems. However, its formalization capability is still limited, which makes it difficult to produce a consistent model; particularly, in the case where several models are combined together. Therefore, using formal verification is an effective...

This paper introduces a virtual laboratory that aims to support the quick development and easy assimilation of practical works by learners and exchange documents between them via a shared virtual space. The proposed laboratory, named 3DVL@ES (web-based 3D virtual laboratory in experimental science), defines an agile design process to automatically...

According to the World Health Organization updates, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic between 2019 and 2022, with millions of confirmed cases and deaths worldwide. There are various approaches to predicting the suspected, infected, and recovered (SIR) cases with different factual or epidemiological m...

A blockchain is a shared database allowing trust to be created between individuals without using intermediaries. The architecture here is decentralized, the data is distributed among the users, and therefore the information can never be erased. Today, many fields are interested in the development of products and technical solutions based on Blockch...

Internet of Drones (IoD) plays a crucial role in the future Internet of Things due to its important features such as low cost, high flexibility, and mobility. The number of IoD applications is drastically increasing from military to civilian fields. Nevertheless, drones are resource-constrained and highly vulnerable to several security threats and...

Software testing is vital to improve software quality. However, software tester role is stigmatized, partly due to misperception and partly due to the treatment of the testing process within the software industry. The present study analyses this situation aiming to explore what might inhibit an individual from taking up a software testing career. I...

Software testing is vital to improve software quality. However, software tester role is stigmatized, partly due to misperception and partly due to the treatment of the testing process within the software industry. The present study analyses this situation aiming to explore what might inhibit an individual from taking up a software testing career. I...

Over the past decade, moving computing and storage processes into cloud data centers has been the trend. However, cloud computing is currently encountering different challenges to meet new requirements of the next wave of the Internet, namely, the Internet of Things (IoT). Fog computing is an emerging paradigm that extends cloud computing services...

Internet of things (IoT) allows the interconnection between physical devices to improve human lives by offering daily services intelligently. The IoT devices are embedded with sensors and actuators to control our physical world and share personal information via wireless channels. To secure data transmission in the IoT, privacy-preserving is highly...

Recent advances in networking and the emergence of the Internet of Things (IoT) have facilitated the development of the Internet of Vehicles (IoV), a distributed network characterized by large number of connected nodes, such as vehicles, roadside units, and smart devices. The large number of nodes may cause problems, such as network congestion, tha...

The IEEE 802.15.4e specified the Time Slotted Channel Hopping (TSCH) that uses multi-channels and shared links to ensure a reliable and efficient data transmission in IoT applications. However, the standard does not define any scheduling mechanism for the network configuration. The main problem in TSCH is triggered when hidden nodes in a shared lin...

Limitations of available literature: Nowadays, coronavirus disease 2019 (COVID-19) is the world-wide pandemic due to its mutation over time. Several works done for covid-19 detection using different techniques however, the use of small datasets and the lack of validation tests still limit their works. Also, they depend only on the increasing the ac...

With the increasing popularity of Cloud computing systems, the demand for highly dependable Cloud applications has increased significantly. For this, reliability and availability of Cloud applications are two prominent issues for both the providers and the users of Cloud. However, ensuring these two properties in Cloud applications is often very di...

The Internet of Things (IoT) and the recent advancements in cloud computing have gained importance with the surge in the amount of data generated globally. Moreover, the rapidly increasing applications of the Internet in many scientific and real-time practical applications have ushered in a new era of complex applications of data flow. Tourism and...

Recently, Zoom and Microsoft Teams have emerged as the most common tools for lecturing activities in higher education institutions. The fact that these platforms were not originally developed for educational purposes resulted in a significant reduction in learning effectiveness, especially in STEM subjects that require a lot of practical knowledge....

The Internet of Things (IoT) represents a pervasive system that continuously demonstrates an expanded application in various domains. The energy efficiency problem has always been a crucial issue linked to this type of network where the system lifetime strongly depends on devices’ batteries. Numerous energy efficient networking protocols have been...

In this work, we present a new nature‐inspired cross‐layer routing protocol named ACO‐based MAC‐aware routing protocol (ACOMAR). An enhancement of time division multiple access (TDMA) algorithm is proposed where slots allocation algorithm considers the geographical distance between nodes and the sink. The nodes that are far away from the sink have...

Detecting at-risk students provides advanced benefits for improving student retention rates, effective enrollment management, alumni engagement, targeted marketing improvement, and institutional effectiveness advancement. One of the success factors of educational institutes is based on accurate and timely identification and prioritization of the st...

Global optimization solves real-world problems numerically or analytically by minimizing their objective functions. Most of the analytical algorithms are greedy and computationally intractable (Gonzalez in Handbook of approximation algorithms and metaheuristics: contemporary and emerging applications, vol. 2. CRC Press, Boca Raton, 2018). Metaheuri...

The Internet of Things (IoT) aims to transform everyday physical objects into an interconnected ecosystem with digital data accessible anywhere and anytime. "Things" in IoT are embedded with sensing, processing and actuating capabilities and cooperate in providing smart and innovative services autonomously. The rapid spread of IoT services arises d...