Mowafaq Salem Alzboon

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Verified

Mowafaq verified their affiliation via an institutional email.

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• Ph.D. in Computer Science
• Professor (Associate) at Jadara University

Social network usage is growing exponentially in the most up-to-date decade; though social networks are becoming increasingly popular every day, many users are continuously active social network users. Using Twitter, LinkedIn, Facebook, and other social media sites has become the most convenient way for people. There is an enormous quantity of data...

Introduction: Personal identification is a critical aspect of forensic sciences, security, and healthcare. While conventional biometrics systems such as DNA profiling and iris scanning offer high accuracy, they are time-consuming and costly. Objectives: This study investigates the relationship between fingerprint patterns and ABO blood group classi...

Identification of a person is central in forensic science, security, and healthcare. Methods such as iris scanning and genomic profiling are more accurate but expensive, time-consuming, and more difficult to implement. This study focuses on the relationship between the fingerprint patterns and the ABO blood group as a biometric identification tool....

This study investigates the application of machine learning (ML) models for classifying dental providers into two categories—standard rendering providers and safety net clinic (SNC) providers—using a 2018 dataset of 24,300 instances with 20 features. The dataset, characterized by high missing values (38.1%), includes service counts (preventive, tre...

Dental provider classification plays a crucial role in optimizing healthcare resource allocation and policy planning. Effective categorization of providers, such as standard rendering providers and safety net clinic (SNC) providers, enhances service delivery to underserved populations. To evaluate the performance of machine learning models in class...

Vesicoureteral reflux (VUR) is traditionally assessed using subjective grading systems, leading to variability in diagnosis. This study explores the potential of machine learning to enhance diagnostic accuracy by analysing voiding cystourethrogram (VCUG) images. The objective is to develop predictive models that provide an objective and consistent...

Brain tumor segmentation based on multi-modal magnetic resonance imaging is a challenging medical problem due to tumors heterogeneity, irregular boundaries, and inconsistent appearances. For this purpose, we propose a hybrid primal and dual ensemble architecture leveraging EfficientNetB4 and MobileNetV3 through a cross-network novel feature interac...

Diabetes has emerged as a significant global health issue, especially with the increasing number of cases in many countries. This trend Underlines the need for a greater emphasis on early detection and proactive management to avert or mitigate the severe health complications of this disease. Over recent years, machine learning algorithms have shown...

In a period where interest in Artificial Intelligence (AI) is rapidly increasing, there remains a notable research gap, especially in the context of AI adoption in Small and Medium Enterprises (SMEs). This study seeks to address this gap by investigating AI acceptance in Jordanian SMEs. Considering Jordan’s cultural environment of high uncertainty...

Phishing remains one of the most dangerous threats to internet users and organizations today since it utilizes spoofed websites to coax users into revealing their data. This paper focuses on the effectiveness of algorithms in detecting such abusive websites. It goes on to analyze the dataset of phishing and non- phishing URLs providing explanatory...

Phishing attacks continue to be a danger in our digital world, with users being manipulated via rogue websites that trick them into disclosing confidential details. This article focuses on the use of machine learning techniques in the process of identifying phishing websites. In this case, a study was undertaken on critical factors such as URL exte...

The diagnosis of tumors in the female reproductive system is crucial for effective treatment and patient outcomes. The advent of artificial intelligence (AI) has introduced new possibilities for enhancing diagnostic accuracy and efficiency. A comprehensive search across PubMed, Scopus, and Web of Science for articles published from 2018 to 2023 on...

The integration of artificial intelligence (AI) in healthcare presents significant promise to enhance clinical procedures and patient outcomes. This research examines the setting, methodology, conclusions, and issues associated with AI in healthcare. The swift proliferation of digital health data, encompassing medical imaging and clinical records,...

This article uses machine learning to quantify vesicoureteral reflux (VUR). VCUGs in pediatric urology are used to diagnose VUR. The goal is to increase diagnostic precision. Various machine learning models categorize VUR grades (Grade 1 to Grade 5) and are evaluated using performance metrics and confusion matrices. Study datasets come from interne...

Parallel programs that require sizeable computational electricity increasingly depend on grid computing structures. Efficient, helpful resource discovery algorithms are critical for optimizing resource allocation and minimizing execution time in these environments. This look presents a unique hierarchical and weighted resource discovery algorithm d...

Gene microarray classification is yet a difficult task because of the bigness of the data and limited number of samples available. Thus, the need for efficient selection of a subset of genes is necessary to cut down on computation costs and improve classification performance. Consistently, this study employs the Correlation-based Feature Selection...

In an era where the military utilization of Unmanned Aerial Vehicles (UAVs) has become essential for surveillance and operational operations, our study tackles the growing demand for real-time, accurate UAV recognition. The rise of UAVs presents numerous safety hazards, requiring systems that distinguish UAVs from non-threatening phenomena, such as...

Numerous studies have highlighted the significance of artificial intelligence (AI) in breast cancer diagnosis. However, systematic reviews of AI applications in this field often lack cohesion, with each study adopting a unique approach. The aim of this study is to provide a detailed examination of AI's role in breast cancer diagnosis through citati...

Brain cancer remains one of the most challenging medical conditions due to its intricate nature and the critical functions of the brain. Effective diagnostic and treatment strategies are essential, particularly given the high stakes involved in early detection. Magnetic Resonance (MR) imaging has emerged as a crucial modality for the identification...

This study conducts an empirical examination of MLP networks investigated through a rigorous methodical experimentation process involving three diverse datasets: TinyFace, Heart Disease, and Iris. Study Overview: The study includes three key methods: a) a baseline training using the default settings for the Multi-Layer Perceptron (MLP), b) feature...

Tobacco smoking keeps to exert a profound effect on cardiovascular health, contributing to situations including arterial stiffness, hypertension, and microcirculatory disorder. Traditional studies strategies, often siloed into remoted domains like biomarker analysis or behavioral surveys, fail to seize the dynamic interplay between smoking behavior...

Smoking remains a global health crisis, contributing to addiction and diverse diseases through complex biological mechanisms. This study explores the hypothesis that smoking induces epigenetic modifications and alters bidirectional neurobiological pathways, perpetuating addiction and disease progression. Leveraging a dataset of 55,692 individuals w...

Oral cancer presents a formidable challenge in oncology, necessitating early diagnosis and accurate prognosis to enhance patient survival rates. Recent advancements in machine learning and data mining have revolutionized traditional diagnostic methodologies, providing sophisticated and automated tools for differentiating between benign and malignan...

Accurate and early diagnosis, coupled with precise prognosis, is critical for improving patient outcomes in various medical conditions. This paper focuses on leveraging advanced data mining techniques to address two key medical challenges: diagnosis and prognosis. Diagnosis involves differentiating between benign and malignant conditions, while pro...

Accurate and early diagnosis, coupled with precise prognosis, is critical for improving patient outcomes in various medical conditions. This paper focuses on leveraging advanced data mining techniques to address two key medical challenges: diagnosis and prognosis. Diagnosis involves differentiating between benign and malignant conditions, while pro...

Landslides can cause severe damage to infrastructure and human life, making early detection and warning systems critical for mitigating their impact. In this study, we propose a machine learning approach for landslide detection using remote sensing data and topographical features. We evaluate the performance of several machine learning algorithms,...

In an era where Unmanned Aerial Vehicles (UAVs) have become crucial in military surveillance and operations, the need for real-time and accurate UAV recognition is increasingly critical. The widespread use of UAVs presents various security threats, requiring systems that can differentiate between UAVs and benign objects, such as birds. This study c...

Artificial intelligence (AI) holds significant potential to revolutionize healthcare by improving clinical practices and patient outcomes. This research explores the integration of AI in healthcare, focusing on methodologies such as machine learning, natural language processing, and computer vision, which enable the extraction of valuable insights...

Diabetes is a chronic disease that affects millions of people worldwide. Early diagnosis and effective management are crucial for reducing its complications. Diabetes is the fourth-highest cause of mortality due to its association with various comorbidities, including heart disease, nerve damage, blood vessel damage, and blindness. The potential of...

In this study, we evaluated the performance of various machine-learning models on multiple datasets labeled GR1, GR2, GR3, GR4, and GR5. We assessed the models using a range of evaluation metrics, including AUC, CA, F1, precision, recall, MCC, specificity, and log loss. The models examined were logistic regression, decision tree, kNN, random forest...

In today’s interconnected world, the transmission of both lengthy and concise text messages is ubiquitous across diverse communication platforms. With the proliferation of sensitive and specialized information being exchanged, safeguarding these messages from potential threats such as intruders, abusers, and data hackers becomes imperative. This st...

Machine Learning methods are beneficial to extract information from the raw data. These methods are applied in numerous fields, such as medicine, education, finance, business, etc. Classification methods are prominent approaches in data mining for predicting the target variable using the independent factors. There are various software mechanisms an...

Detection and management of diabetes at an early stage is essential since it is rapidly becoming a global health crisis in many countries. Predictions of diabetes using machine learning algorithms have been promising. In this work, we use data collected from the Pima Indians to assess the performance of multiple machine-learning approaches to diabe...

As time goes by, hospitals are now facing an era of global competition in various medical fields. The rapid development of science and technology in the medical field has created competition between hospitals. This increasingly fierce competition requires hospitals to provide the best service. This study aims to determine the public relations strat...

Heart disease is the leading cause of mortality worldwide. Early identification and prediction can play a crucial role in preventing and treating it. Based on patient data, machine learning techniques may be used to construct cardiac disease prediction models. This work aims to investigate the usage of machine learning models for heart disease pred...

The advancement of technology in sensors and communication devices to the Internet has resulted in practical solutions in various networking sectors, public and private sector enterprises, and government organizations worldwide. In addition, the widespread use of Smart Devices and Mobile Technologies in the healthcare industry has enhanced their gl...

In the last decade, a significant number of people have become active social network users. People utilize Twitter, Facebook, LinkedIn, and Google+. Facebook users generate a lot of data. Photos can teach people a lot. Image analysis has traditionally focused on audience emotions. Photographic emotions are essentially subjective and vary among obse...

Billions of people interact with social media daily. However, various users realize how every snap and press produced interactions eventually led to a large social network structure. Enthusiastic social media users, including mailings, pages, microblogs, and wikis, are willing to send personal or public messages, express strong views, raise awarene...

The services of the Video on Demand (VoD) are currently based on the developments of the technology of the digital video and the network’s high speed. The files of the video are retrieved from many viewers according to the permission, which is given by VoD services. The remote VoD servers conduct this access. A server permits the user to choose vid...

Shared computing infrastructures such as Peer-to-Peer (P2P) networks and grid technologies allow sharing resources between a large amount of geographically and dynamically distributed resources to achieve an efficient degree of the performance of supercomputing. The main issue of this performance refers to the resource discovery as it is considered...

Outsourcing logistics has established itself in the area of the LSP (Logistics Service Provider), which offers a range of services to its customers. In this line, transportation is characterized as one of the most important services, and therefore efficient fleet management is essential for establishing a high level of customer service. In this pap...

The increased number of computers, enlarged network bandwidth, more powerful computers, consumed resources and the acceptance of the Internet has driven the ongoing demand for new and better ways to execute huge problems in shared computing infrastructure such as grid and P2P computing. Resource discovery is extremely significant and challenging is...

In intelligent transportation systems, broadcasting Warning Messages (WMs) by Vehicular Ad hoc Networks (VANETs) communication is a significant task. Designing efficient dissemination schemes for fast and reliable delivery of WMs is still an open research question. In this paper, we propose a novel messaging scheme, Advanced Speed and Density Warni...

Gene microarray classification problems are considered a challenge task since the datasets contain few number of samples with high number of genes (features). The genes subset selection in microarray data play an important role for minimizing the computational load and solving classification problems. In this paper, the Correlation-based Feature Se...

Introduction: The most important properties of the proposed concept in the quality of information and evaluation it is procedure is universality, significantly expanding the class of problems to be solved information analysis. The intensification of the development of the national economy directly affects high education as one of the links in the s...

The Video on Demand (VOD) system is considered a communicating multimedia system that can allow clients be interested whilst watching a video of their selection anywhere and anytime upon their convenient. The design of the VOD system is based on the process and location of its three basic contents, which are: the server, network configuration and c...

Introduction: The most important properties of the proposed concept in the quality of information and evaluation it is procedure is universality, significantly expanding the class of problems to be solved information analysis. The intensification of the development of the national economy directly affects high education as one of the links in the s...

Internet of Things is considered to represent a platform in which daily devices and their processing get more intelligent than ever where daily communications get further informative. While the Internet of Things remains searching its particular shape, its influences have gazed in producing inconceivable steps as a universal solution media pertaini...

The world's population development and high needs for limited goods are the results of proposing the need for further effective use of various resources and materials. Since current improvements in Information and Communication Technology (ICT) have entirely transformed massive regions, their use brings a negative effect on the environment and huma...

Internet-based distributed systems allow resources, which are distributed extensively in the network to be utilized cooperatively and shared to enable the end-user to get a massive computational power to tackle a huge task. Hence, the crucial role of resource discovery comes. Even though several mechanisms have been proposed to detect the multi-att...

We present a mechanism, Self Resource Discovery Mechanism (SRDM) with the aim of offers scalable, decentralized resource discovery and load balancing for sharing computing via huge pools of various nodes. Primarily, SRDM hides the resources values for each node in the system in the configuration of the links linking the nodes. This distributed hidi...

Global computational grids nowadays are suffered from ossification problems due to the following fundamental challenges related to different existing solutions in grid computing: scalability, adaptability, security, reliability, availability and manageability. The management difficulty is due to heterogeneity, dynamicity and locality of the resourc...

Overlay networks are virtual networks built on top of the physical computer networks. A special kind of these networks is built specifically to meet specific user's requirements. They are called Services Specific Overlay Networks (SSON). Managing and achieving load balancing in such environment is challenging. This challenge is always increasing as...