Abdullah Baqasah

• Doctor of Philosophy
• Professor (Assistant) at Taif University

As healthcare rapidly digitalizes, cloud computing has emerged as the backbone of modern medical data storage and processing, owing to its scalability, cost-efficiency, and universal accessibility. Despite these advantages, centralized cloud infrastructures inherently suffer from significant drawbacks, particularly in protecting patient privacy, en...

Accurate air quality forecasting is critical for human health and sustainable atmospheric management. To address this challenge, we propose a novel hybrid deep learning model that combines cutting-edge techniques, including CNNs, BiLSTM, attention mechanisms, GNNs, and Neural ODEs, to enhance prediction accuracy. Our model uses the Air Quality Open...

Heart disease remains the leading cause of death globally, mainly caused by delayed diagnosis and indeterminate categorization. Many of traditional ML/DL methods have limitations of misclassification, similar features, less training data, heavy computation, and noise disturbance. This study proposes a novel methodology of Modified Multiclass Attent...

Accurate segmentation of brain tumors from multimodal Magnetic Resonance Imaging (MRI) plays a critical role in diagnosis, treatment planning, and disease monitoring in neuro-oncology. Traditional methods of tumor segmentation, often manual and labour-intensive, are prone to inconsistencies and inter-observer variability. Recently, deep learning mo...

The rapid growth of cloud computing has brought scalability and flexibility to modern organizations, but it has also introduced a new wave of complex and evolving security threats. Traditional security mechanisms, such as static rule-based systems and Multi-Factor Authentication (MFA), often fall short of identifying advanced attacks like insider t...

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...

The Internet of Things (IoMT) has revolutionized the global landscape by enabling the hierarchy of interconnectivity between medical devices, sensors, and healthcare applications. Significant limitations in terms of scalability, privacy, and security are associated with this connection. This study presents a scalable, lightweight hybrid authenticat...

Biosensors are crucial to the diagnosis process since they are designed to detect a specific biological analyte by changing from a biological entity into electrical signals that can be processed for further inspection and analysis. The method provides stability while evaluating cancer cell imaging and real-time angiogenesis monitoring, together wit...

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...

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...

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...

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...

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,...

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...

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...

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...

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...

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...

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...

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...

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,...

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...

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...

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...

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

Industrial automation systems are undergoing a revolutionary change with the use of Internet-connected operating equipment and the adoption of cutting-edge advanced technology such as AI, IoT, cloud computing, and deep learning within business organizations. These innovative and additional solutions are facilitating Industry 4.0. However, the emerg...

Speckle noise is a pervasive problem in medical imaging, and conventional methods for despeckling often lead to loss of edge information due to smoothing. To address this issue, we propose a novel approach that combines a nature-inspired minibatch water wave swarm optimization (NIMWVSO) framework with an invertible sparse fuzzy wavelet transform (I...

Hepatitis C Virus (HCV) is a viral infection that causes liver inflammation. Annually, approximately 3.4 million cases of HCV are reported worldwide. A diagnosis of HCV in earlier stages helps to save lives. In the HCV review, the authors used a single ML-based prediction model in the current research, which encounters several issues, i.e., poor ac...

Fruits significantly impact everyday living, i.e., Citrus fruits. Numerous fruits have a solid nutritious value and are packed with multivitamins and trace components. Citrus fruits are delicate and susceptible to many diseases and infections. Many researchers have suggested deep and machine learning-based fruit disease detection and classification...

In order to improve the library's information retrieval and resource sharing capabilities and establish an intelligent library information management system, this paper proposes a library information management system development technology based on data mining technology. The system development is divided into two modules: library information retr...

Classification of remote scenes in satellite imagery has many applications, such as surveillance, earth observation, etc. Classifying high-resolution remote sensing images in machine learning is a big challenge nowadays. Several automated techniques based on machine learning and deep learning have been introduced in the literature; however, these t...

To study smart data collection and network error analysis, this paper proposes intelligent data collection and network error analysis based on artificial intelligence. It examines the establishment of an enterprise-level information security situation awareness system and proposes specific information security models, architectures, and implementat...

In the modern world, it is difficult to prevent terrorism due to the relatively closed environment, dense personnel, large passenger flow, long line and wide coverage of urban rail transit. Identity recognition is a core element of security. The design and study of an urban rail transit security system based on face recognition technology are propo...

Underwater wireless sensor networks (UWSNs) have emerged as the most widely used wireless network infrastructure in many applications. Sensing nodes are frequently deployed in hostile aquatic environments in order to collect data on resources that are severely limited in terms of transmission time and bandwidth. Since underwater information is very...

Due to the complexity and versatility of network security alarm data, a cloud-based network security data extraction method is proposed to address the inability to effectively understand the network security situation. The information properties of the situation are generated by creating a set of spatial characteristics classification of network se...

For a better detection in Network information security monitoring system, the author proposes a method based on adaptive depth detection. A deep belief network (DBN) was designed and implemented, and the intrusion detection system model was combined with a support vector machine (SVM). The data set adopts the NSL-KDD network communication data set,...

Diabetic Retinopathy (DR) is a predominant cause of visual impairment and loss. Approximately 285 million worldwide population is affected with diabetes, and one-third of these patients have symptoms of DR. Specifically, it tends to affect the patients with 20 years or more with diabetes, but it can be reduced by early detection and proper treatmen...

Advancement in technology has led to innovation in equipment, and the number of devices is increasing every day. Industries are introducing new devices every day and predicting 50 billion connected devices by 2022. These devices are deployed through the Internet, called the Internet of Things (IoT). Applications of IoT devices are weather predictio...

In the pandemic of COVID-19, it is crucial to consider the hygiene of the edible and nonedible things as it could be dangerous for our health to consume infected things. Furthermore, everything cannot be boiled before eating as it can destroy fruits and essential minerals and proteins. So, there is a dire need for a smart device that could sanitize...

Distributed Denial of Service (DDoS) attack is known to be one of the most lethal attacks in traditional network architecture. In this attack, the attacker uses botnets to overwhelm network resources. Botnets can be randomly compromised computers or IoT devices that are used to generate excessive traffic towards the victim, and as a result, legitim...

Designing an efficient, reliable, and stable algorithm for underwater acoustic wireless sensor networks (UA-WSNs) needs immense attention. It is due to their notable and distinctive challenges. To address the difficulties and challenges, the article introduces two algorithms: the multilayer sink (MuLSi) algorithm and its reliable version MuLSi-Co u...

Aiming to increase the shelf life of food, researchers are moving toward new methodologies to maintain the quality of food as food grains are susceptible to spoilage due to precipitation, humidity, temperature, and a variety of other influences. As a result, efficient food spoilage tracking schemes are required to sustain food quality levels. We ha...