Roobaea Alroobaea

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• Professor in Computer Science. Taif University Saudi Arabia
• Professor at Taif University

The electronic information revolution and the use of computers as an essential part of everyday life are now more widespread than ever before, as the Internet is exploited for the speedy transfer of data and business. Hotel/hospitality websites are growing in use worldwide, and they present popular business channels on the Internet. However, they n...

There are some key problems faced in modern agriculture that IoT-based smart farming. These problems such shortage of water, plant diseases, and pest attacks. Thus, artificial intelligence (AI) technology cooperates with the Internet of Things (IoT) toward developing the agriculture use cases and transforming the agriculture industry into robustnes...

Skin cancer represents a significant global public health issue, and prompt and precise detection is essential for effective treatment. This study introduces SkinEHDLF, an innovative deep-learning model that enhances skin cancer classification. SkinEHDLF utilizes the advantages of several advanced models, i.e., ConvNeXt, EfficientNetV2, and Swin Tr...

Numerous privacy and security concerns could jeopardize the social media ecosystem: mishandled hotspot connectivity used as a standalone cybercrime; illegal campaigning; deviant activities conducted online; propagation of anti-national propaganda; and recruitment of terrorists through social media platforms. These provide significant challenges for...

Breast cancer detection remains one of the most challenging problems in medical imaging. We propose a novel hybrid model that integrates Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory (Bi-LSTM) networks, and EfficientNet-B0, a pre-trained model. By leveraging EfficientNet-B0, which has been trained on the large and diver...

Functional requirements (FRs) prioritization is process of ranking of software FRs from development perspective such that which requirement to be implemented first and which should not. FRs prioritization is necessary as these requirements are interrelated such that one requirement is necessary for the implementation of another requirement. Also, w...

Cryptocurrency represents a form of asset that has arisen from the progress of financial technology, presenting significant prospects for scholarly investigations. The ability to anticipate cryptocurrency prices with extreme accuracy is very desirable to researchers and investors. However, time-series data presents significant challenges due to the...

In this paper, the author introduces the Neural-ODE Hybrid Block Method, which serves as a direct solution for solving higher-order ODEs. Many single and multi-step methods employed in numerical approximations lose their stability when applied in the solution of higher-order ODEs with oscillatory and/or exponential features, as in this case. A new...

Geothermal energy, a renewable and sustainable resource, has significant potential for meeting global energy demands; most of the study on production and generation relies on numerical simulation. However, the computational intensity of physics-based numerical simulations for geothermal energy production poses challenges. This study explores the in...

Melanoma is a malignant tumor originating from skin cell lesions. Accurate and efficient segmentation of skin lesions is essential for quantitative medical analysis but remains challenging. To address this, we propose ScaleFusionNet, a segmentation model that integrates Cross-Attention Transformer Module (CATM) and AdaptiveFusionBlock to enhance fe...

Due to significance such as reduce cost and time, clients and vendors rely mostly on Global Software Development (GSD) in modern era. Due to geographical distance, there exist culture, language and time zone differences among clients and vendors in GSD. In GSD, requirement engineering phase is considered as very critical as it deals with all aspect...

The rapidly evolving field of transport systems is further changing with the integration of blockchain distributed ledger technology, artificial intelligence (AI), and the Internet of Things (IoT). This integration not only enables automation but also promotes the development of cooperative intelligent transport systems. Despite these advancements,...

In the dynamic environment of the Internet of Things (IoT), edge and cloud computing play critical roles in analysing and storing data from numerous connected devices to produce valuable insights. Efficient resource allocation and workload distribution are vital to ensuring continuous and reliable service in growing IoT ecosystems with increasing d...

Advanced technologies like Cyber-Physical Systems (CPS) and the Internet of Things (IoT) have supported modernizing and automating the transportation region through the introduction of Intelligent Transportation Systems (ITS). Integrating CPS-ITS and IoT provides real-time Vehicle-to-Infrastructure (V2I) communication, supporting better traffic man...

In this work, the separation of variables approach is employed to investigate and assess analytical stream function solutions for two‐dimensional incompressible couple stress fluid flow. The suggested method involves transforming the governing partial differential equations (PDEs) of fluid flow into ordinary differential equations (ODEs) by assumin...

Purpose of Review This paper summarizes recent literature on the pandemic's effects on IS treatment. The literature is searched in popular databases, including PubMed, ScienceDirect, Springer, Wiley Online, and Google Scholar. Cerebral infarction (CI) or ischemic stroke (IS) refer to a stroke caused by the blockage of blood in the brain. Ischemic s...

This paper analyzes Step Density Modulation (SDM) technique for high-frequency inverters in Wireless Power Transfer(WPT) systems for Electric Vehicle (EV) charging. While Pulse Density Modulation (PDM) is commonly used to control high-frequency inverters, it faces limitations in managing current ripple, leading to electromagnetic interference (EMI)...

EM) presents significant challenges in securely managing and exchanging information. This study introduces a blockchain-based platform, BAIoT-EMS, designed to enhance security and efficiency in AIoT-enabled EM systems. The platform leverages a consortium network and InterPlanetary File Storage (IPFS) for secure storage and transaction management, s...

The integration of artificial intelligence (AI) has caused information and communication technology (ICT) to undergo a number of recent rapid fluctuations. These changes have primarily affected the areas of management, end-to-end device interconnectivity, resource organization, communication, networking, and application-related aspects of ICT. Owin...

Despite tremendous improvements in sensing mechanisms at the hardware level, sensor drift is still an issue for reliable IoT applications. Existing literature is limited in exploring the impacts of sensing contexts on sensor drift and handling sensor drift using soft computing approaches. The study intends to propose a fog-enabled IoT architecture...

Consumer product recognition involves utilizing computer vision (CV) and machine learning (ML) systems for identifying and recognizing numerous consumer goods in video or image frames. This technology determines applications in retail, e-commerce, security systems, and inventory management. The purpose is to automate the detection of certain produc...

Medical professionals primarily utilize medical images to detect anomalies within the interior structures and essential organs concealed by the skeletal and dermal layers. The primary purpose of medical imaging is to extract image features for the diagnosis of medical conditions. The processing of these images is indispensable for evaluating a pati...

The rapid adoption of Unmanned Aerial Vehicles (UAVs) in the construction industry has revolutionized safety, surveying, quality monitoring, and maintenance assessment. UAVs are increasingly used to prevent accidents caused by falls from heights or being struck by falling objects by ensuring workers comply with safety protocols. This study focuses...

Heart disease is a leading cause of death globally; therefore, accurate detection and classification are prominent, and several DL and ML methods have been developed over the last decade. However, the classical approaches may be prone to overfitting and under fitting issues, and the model performance may lag due to the unavailability of annotated d...

Microorganism movement may boost the convective transfer of heat by stirring the fluid to encourage mixing. Engineers may improve heat dissipation and maintain temperatures in electrical devices, engines, and industrial machinery by varying microbe proportion and quality. This research aims to gain insight into the rheological effects of an Eyring–...

Protein–protein interaction (PPI) prediction is vital for interpreting biological activities. Even though many diverse sorts of data and machine learning approaches have been employed in PPI prediction, performance still has to be enhanced. As a result, we adopted an Aquilla Influenced Shark Smell (AISSO)-based hybrid prediction technique to constr...

This research seeks to explore the behavior of Ree–Eyring nanofluid over an extended surface influenced by an inclined magnetic field within a permeable medium. The local thermal non‐equilibrium between the particle, liquid, and solid phases is represented by a three‐temperature model. The problem is addressed numerically using bvp4c code in MATLAB...

Regenerative braking is of paramount importance both in terms of energy recovery and from the perspective of hybrid electric vehicles (HEVs). It allows HEVs to recover energy during braking which in turn enhances the range, efficiency and sustainability by reducing electricity demand and environmental impacts. Upon considering the demand for high-p...

Cybertwin (CT) is an innovative network structure that digitally simulates humans and items in a virtual environment, significantly influencing Cybertwin instances more than regular VMs. Cybertwin-driven networks, combined with Mobile Edge Computing (MEC), provide practical options for transmitting IoT-enabled data. This research introduces a hybri...

Wireless Body Sensor Network (WBSN) has gained increasing attention in health monitoring and service sector for real-time health monitoring and providing high-quality service. 6G wireless communication technologies overcome the limitations of the current 5G technology. An intelligent security system that prevents DDoS attack by applying solutions b...

Due to the aquatic nature of communication in the underwater world, the underwater acoustic sensor network (UASN) is commonly used. However, it has inherent limitations, such as limited bandwidth, high transmission energy, long propagation delays, void regions, and expensive battery replacement. Improving network lifetime (NL) is the primary object...

This paper introduces a groundbreaking method, Homotopy-based Fourier transform, integrating Fourier transform and Homotopy perturbation for refined nonlinear problem-solving. The modification enhances solution technique efficiency, notably accelerating convergence, particularly in solving the Korteweg–de Vries equation. Demonstrating versatility,...

Foreign object debris (FOD) includes any unwanted and unintentional material lying on the charging lane or parking lots, posing a risk to the wireless charging system, the vehicle, or the people inside. FOD in an Electric Vehicle (EV) wireless charging system can cause problems, including decreased charging efficiency, safety risks, charging system...

The perturbed nonlinear Schrödinger equation is employed to characterize the dynamics of optical wave propagation when confronted with dissipation (or gain) and nonlinear dispersion that vary with both time and space. This equation serves as a fundamental model for investigating pulse dynamics within optical fibers and has application to nanofiber...

With the continuous advancements in artificial intelligence, human activity recognition (HAR) technologies have garnered widespread attention and found applications across diverse domains. Recently, various features and deep learning models are proposed for human activity recognition using sensors data. Though the existing models and features have...

This study introduces the Harmonic Mean Optimizer (HMO), a novel meta-heuristic algorithm designed to address complex global optimization problems. The primary objective of this research is to develop an optimization technique that effectively balances exploration and exploitation without requiring extensive parameter tuning, thereby simplifying th...

Recent advancements in image processing and machine-learning technologies have significantly improved vehicle monitoring and identification in road transportation systems. Vehicle classification (VC) is essential for effective monitoring and identification within large datasets. Detecting and classifying vehicles from surveillance videos into vario...

The communication barriers experienced by deaf and hard-of-hearing individuals often lead to social isolation and limited access to essential services, underlining a critical need for effective and accessible solutions. Recognizing the unique challenges this community faces—such as the scarcity of sign language interpreters, particularly in remote...

This investigation uses the Tiwari and Das nanofluid model to enhance the heat transfer rate in Sutterby nanofluid over a Riga plate. The effects of heat source/sink, viscosity dispersion, and mass flow for water-based fluids are also considered in this work. Sutterby fluid has been utilized to investigate the rheological features of nanofluids. Th...

Particularly in the context of smart cities, remote sensing data (RSD) has emerged as one of the hottest study topics in information and communication technology (ICT) today. The development of machine learning (ML) and artificial intelligence (AI) has made it possible to solve a number of issues, including automation, control access, optimization,...

In smart cities, air pollution is a critical issue that affects individual health and harms the environment. The air pollution prediction can supply important information to all relevant parties to take appropriate initiatives. Air quality prediction is a hot area of research. The existing research encounters several challenges that is, poor accura...

The agricultural sector emphasizes sustainable development and energy efficiency, particularly in optimizing water pumping systems for irrigation. Brushless DC (BLDC) motors are the preferred prime mover over induction motors due to their high efficiency in such applications. This article details the rotor design and analysis of an energy-efficient...

The Traditional hospital manual-centric focused model has been replaced with the decentralised patient-centric approach in recent data processing models. The advent of the 6G communication model makes high data rate transmission in less time for remote healthcare services. As healthcare applications grow, data are generated in numerous forms and si...

The difficulty of collecting maize leaf lesion characteristics in an environment that undergoes frequent changes, suffers varying illumination from lighting sources, and is influenced by a variety of other factors makes detecting diseases in maize leaves difficult. It is critical to monitor and identify plant leaf diseases during the initial growin...

The surge in demand for eco-friendly transportation and electric vehicle (EV) charging infrastructure necessitates innovative solutions. This study proposed a novel approach to charging slow-moving vehicles, prioritizing efficiency and minimizing output pulsation. Central to the research is the development of a receiver-side power-regulated constan...

Autonomous decision-making is considered an intercommunication use case that needs to be addressed when integrating open radio access networks with mobile-based 5G communication. The robustness of innovations is diminished by the conventional method of designing an end-to-end radio access network solution. Through an analysis of these possibilities...

Similarity measures and distance measures are used in a variety of domains, such as data clustering, image processing, retrieval of information, and recognizing patterns, in order to measure the degree of similarity or divergence between elements or datasets. p,q− quasirung orthopair fuzzy (p,q− QOF) sets are a novel improvement in fuzzy set theory...

The traditional Control Shed Poultry Farm (CSPF) systems are operated manually or in a semi-automatic culture. The existing CSPF system is still not free from human intervention and needs 24/7 monitoring. The existing approach is laborious, prone to caretakers bias and human error, and repeatability is difficult. The Intelligent CSPF system is base...

This study aims to analyze the solution of a system of differential equations that describes the mathematical modeling of cell population dynamics in colonic crypt and colorectal cancer. The Caputo–Fabrizio fractional order derivatives are used to fractionalize the model. The corresponding mathematical model is solved by the Laplace transform, whic...

In recent years, the surge in online content has necessitated the development of intelligent recommender systems capable of offering personalized suggestions to users. However, these systems often encapsulate users within a “filter bubble”, limiting their exposure to a narrow range of content. This study introduces a novel approach to address this...

Vlogs, Recordings, news, sport coverages are huge sources of multimodal information that do not just limit to text but extend to audio, images and videos. Applications such as summary generation, image/video captioning, multimodal sentiment analysis, cross modal retrieval requires Computer Vision along with Natural Language Processing techniques to...

This analysis considers the magnetized third-grade fluid stream and microorganisms over a non-linear stretchy cylinder. The radiation impacts are taken into consideration. The effects of the governing flow at the cylinder are represented in the form of PDEs employing boundary layer approximations. The system of the PDEs is further reduced in dimens...

This study presented a new approach to seizure classification utilizing electroencephalogram (EEG) data. We introduced the NeuroWave-Net, an innovative hybrid model that seamlessly integrates convolutional neural networks (CNN) and long short-term memory (LSTM) architectures. Unlike conventional methods, our model capitalized on CNN's proficiency i...

The Industrial Internet of Things (IIoT) has revolutionized several industries by improving the communication of sensor data among interconnected machines and systems. IIoT frameworks, on the other hand, can be challenging to set up and keep functioning several times. This paper introducing Task Offloading (TO) into the Internet of Things (IoT) bri...

Recent research has focused on applying blockchain technology to solve security-related problems in Internet of Things (IoT) networks. However, the inherent scalability issues of blockchain technology become apparent in the presence of a vast number of IoT devices and the substantial data generated by these networks. Therefore, in this paper, we us...

Significance: The thermal energy transfer in nanofluid flow over an exponentially stretching surface has crucial practical configurations in various industrial processes, and it has potential applications in heat exchangers, chemical engineering, energy harvesting, and material processing. Purpose: This study is devoted to exploring the features of...

The steady MHD boundary-layer axis-symmetric flow of a third-grade fluid passing through an exponentially expanded cylinder in the vicinity of a magnetic field is investigated in this study. The problem is mathematically modeled. Suitable similarity transformations are carried out to convert the partial differential equations into nonlinear ordinar...

Software testing is an important phase as it ensures the software quality. The software testing process comprises of three steps: generation, execution, and evaluation of test cases. Literature claims the usage of single and multiple 'Unified Modeling Language' (UML) diagrams to generate test cases. Using multiple UML diagrams increases test case c...

The paper’s primary goal is to investigate mass and heat transfer processes in reactive nanofluid particles. Within Buongiorno’s model, three chemical reactions are discussed. The main subject is on the nanoparticle fractions at the boundary. The characteristics of Nt and Nb with regard to the nanoparticle fraction have been found to be passively r...

The (3+1)-dimensional double sine-Gordon equation plays a crucial role in various physical phenomena, including nonlinear wave propagation, field theory, and condensed matter physics. However, obtaining exact solutions to this equation faces significant challenges. In this article, we successfully employ a modified $$ \left( \dfrac{G'}{G^2}\right)...

The robust development of the blockchain distributed ledger, the Internet of Things (IoT), and fog computing-enabled connected devices and nodes has changed our lifestyle nowadays. Due to this, the increased rate of device sales and utilization increases the demand for edge computing technology with collaborative procedures. However, there is a wel...

This study investigates the flow and heat transfer characteristics of a second‐grade fluid over a flat surface with variable heat flux. Utilizing a mathematical model based on distributed order fractional derivatives, we offer a more precise representation of non‐Newtonian fluid behavior. The associated highly nonlinear equations are tackled numeri...

This research concerns examining the non-Newtonian blood flow behavior through an artery of elliptic cross-section, affected by several stenoses. The Rabinowitsch fluid model is used to investigate the non-Newtonian behavior of the blood for uniform and nonuniform shapes of stenosis. The mathematical equations have been converted into a dimensionle...

This novel study unfolds the heat and mass transfer investigation of Williamson nanofluid (WNF) through a porous medium past a stretching plate, along with considering heat generation/absorption. Nanoparticles hold significant significance in thermal engineering, industrial operations, and biomedical advancements, contributing to enhanced heat tran...

Postpartum Depression Disorder (PPDD) is a prevalent mental health condition and results in severe depression and suicide attempts in the social community. Prompt actions are crucial in tackling PPDD, which requires a quick recognition and accurate analysis of the probability factors associated with this condition. This concern requires attention....

Skin cancer is a frequently occurring and possibly deadly disease that necessitates prompt and precise diagnosis in order to ensure efficacious treatment. This paper introduces an innovative approach for accurately identifying skin cancer by utilizing Convolution Neural Network architecture and optimizing hyperparameters. The proposed approach aims...

Virtual machine (VM) integration methods have effectively proven an optimized load balancing in cloud data centers. The main challenge with VM integration methods is the trade-off among cost effectiveness, quality of service, performance, optimal resource utilization and compliance with service level agreement violations. Deep Learning methods are...

Recent research has focused on applying blockchain technology to solve security-related problems in Internet of Things (IoT) networks. However, the inherent scalability issues of blockchain technology become apparent in the presence of a vast number of IoT devices and the substantial data generated by these networks. Therefore, in this paper, we us...

Malicious assaults and information leakage have grown in importance in practically every area of information and communication technology (ICT) in recent years. Enterprise ledger organization, preservation, security, and protection are all greatly aided by information security (IS). To maintain their positions in the market, industries must safegua...

AI-driven precision agriculture applications can benefit from the large data source that remote sensing provides, as it can gather agricultural monitoring data at various scales throughout the year. Numerous advantages for sustainable agricultural applications, including yield prediction, crop monitoring, and climate change adaptation, can be obtai...

The inclusion of nanoparticles has the potential to enhance the thermal efficiency of the base fluid. The field of nanofluid dynamics has attracted significant attention due to its wide range of practical applications such as fuel cells, solar energy, medication administration, heat transfer, microfabrication, coolant applications, and other relate...

The integration of Internet of Things (IoT) technology in precision agriculture offers substantial potential for improving productivity and crop yield. However, challenges persist in optimizing wireless solutions for outdoor smart farms, where diverse data types and environmental obstacles can impede efficiency, causing issues such as data loss and...

Presents corrections to the paper, (Corrections to “A New Trend in Cryptographic Information Security for Industry 5.0: A Systematic Review”).