Software Engineering Commons^™

A Novel Multi-Model Patient Similarity Network Driven By Federated Data Quality And Resource Profiling, Alramzana Nujum Navaz

Dissertations

Smart and Connected Health (SCH) is revolutionizing healthcare by leveraging extensive healthcare data for precise, personalized medicine. At its core, SCH relies on the concept of patient similarity, which involves the comparative analysis of newly encountered patients with those who exhibit comparable similarities from the existing patient cohort. Yet, this approach faces significant challenges, including data heterogeneity and dimensionality. Our research introduces a multi-dimensional Patient Similarity Network (PSN) Fusion model tailored to handle both static and dynamic features. The static data analysis focuses on extracting contextual information using Bidirectional Encoder Representations from Transformers (BERT), while dynamic features are captured through …

Enhancing Autism Education: Exploring Interactive Videos And Ai Integration For Effective Teaching, Fatima Ahmed Alraeesi

Thesis/ Dissertation Defenses

Teachers should be aware of how to develop effective teaching methods for students with autism. To achieve the best results, teachers need to thoroughly understand autism and the teaching methods and modifications that work best for these students. Adapting classwork & homework and helping students with language difficulties are effective teaching methods. Teachers can use books to get the necessary information and guidance or take training courses. Keeping students organized and focused is one of the needs of children with autism, as well as the use of visual strategies. Some teachers rely on fixed routines in teaching autistic children. Therefore, …

The Combination Approaches For One Class Classifier Ensembles For Software Defect Datasets, Maitha Mohammed Alkalbani

Theses

The classification of imbalanced datasets poses significant challenges, becoming a crucial topic in ML, particularly when standard algorithms struggle with accurate classification. In OCC, classifiers may encounter objects from ensembles of one class, leading to outlier scores generated at different scales. Additionally, there is a lack of a unified combination method, with many experiments resorting to using an average as the combination method. The thesis aims to investigate the effectiveness of normalization and unnormalized outlier scores on OCC ensembles. Furthermore, we conducted a comparative study of different types of combination methods. We used k-means clustering as OCC model, and the …

Enhancing Autism Education: Exploring Interactive Videos And Ai Integration For Effective Teaching, Fatima Ahmed Alraeesi

Theses

This research focuses on enhancing autism education by integrating interactive videos and AI solutions to improve teacher training. As the number of autistic students rises, it becomes crucial for special education teachers to employ effective teaching strategies tailored to individual needs. The most effective teaching methods for autistic students involve understanding the condition and incorporating customized instruction strategies, such as adapting assignments to suit the student's needs, assisting those with difficulty speaking, and employing visual aids for better organization. The proposed solution involves utilizing interactive video technology to train teachers, bridging the gap between research and practical implementation of educational …

Stream-Evolving Bot Detection Framework Using Graph-Based And Feature-Based Approaches For Identifying Social Bots On Twitter, Eiman Alothali

Dissertations

This dissertation focuses on the problem of evolving social bots in online social networks, particularly Twitter. Such accounts spread misinformation and inflate social network content to mislead the masses. The main objective of this dissertation is to propose a stream-based evolving bot detection framework (SEBD), which was constructed using both graph- and feature-based models. It was built using Python, a real-time streaming engine (Apache Kafka version 3.2), and our pretrained model (bot multi-view graph attention network (Bot-MGAT)). The feature-based model was used to identify predictive features for bot detection and evaluate the SEBD predictions. The graph-based model was used to …

Blockchain-Enabled Ehr Sharing In Healthcare Federation: Sharding And Interblockchain Communication, Faiza Hashim

Dissertations

Electronic Health Records (EHRs) are crucial components of the healthcare system, facilitating accurate and efficient diagnosis. Blockchain technology has emerged as a promising solution to improve EHRs sharing among medical practitioners while ensuring privacy and security. By leveraging its decentralized, distributed, immutable, and secure architecture, blockchain has the potential to revolutionize the healthcare system. However, due to security concerns, blockchain networks in healthcare typically operate in private or consortium modes, resulting in isolated networks within a federation. Scalability remains a significant challenge for blockchain networks, as the number of participating nodes increases within each network of the federation. Consensus mechanisms …

Data-Driven Modeling Of Student Performance In The Time Of Distance Learning, Iman Saad Megdadi

Theses

One of the important aspects that all academic institutions work towards improving is Student Performance. It is obviously the primary indicator of success or failure of institutions. Student performance predictions are vital to instructors and educational decision makers to help, across all levels, tailor learning according to the students’ needs. Therefore, it is essential for Higher Education Institutions to predict student performance in distance learning which has been, and remains, the primary method of learning in some countries due to Corona Virus pandemic. For this reason, this research is going to predetermine a fitting definition of student performance in time …

Interactive Emirate Sign Language E-Dictionary Based On Deep Learning Recognition Models, Ahmed Abdelhadi Abdelhadi

Theses

According to the ministry of community development database in the United Arab Emirates (UAE) about 3065 people with disabilities are hearing disabled (Emirates News Agency - Ministry of Community Development). Hearing-impaired people find it difficult to communicate with the rest of society. They usually need Sign Language (SL) interpreters but as the number of hearing-impaired individuals grows the number of Sign Language interpreters can almost be non-existent. In addition, specialized schools lack a unified Sign Language (SL) dictionary, which can be linked to the Arabic language being of a diglossia nature, hence many dialects of the language co-exist. Moreover, there …

Ureca – The Research Ethics And Data Protection Online Review Platform Used By The University Of Malta, Joel Azzopardi

The Journal of Electronic Theses and Dissertations

Nowadays, research ethics and data protection are given very high importance, and research organizations, including universities, need to safeguard their level of professionalism and integrity by providing the necessary guidelines. Moreover, they need to ensure that these guidelines are being adhered to by their affiliated researchers, including students. This is needed for protection of the research subjects, researchers, and the organization (university) itself. However, care must be taken so that the research ethics review process is streamlined as much as possible to minimize bureaucracy, as such guidelines would then be viewed as a research barrier. This study describes URECA, the …

Identification Of Students At Risk Of Low Performance By Combining Rule-Based Models, Enhanced Machine Learning, And Knowledge Graph Techniques, Balqis Mubarak Al Braiki

Dissertations

Technologies and online learning platforms have changed the contemporary educational paradigm, giving institutions more alternatives in a complex and competitive environment. Online learning platforms, learning-based analytics, and data mining tools are increasingly complementing and replacing traditional education techniques. However, academic underachievement, graduation delays, and student dropouts remain common problems in educational institutions. One potential method of preventing these issues is by predicting student performance through the use of institution data and advanced technologies. However, to date, scholars have yet to develop a module that can accurately predict students’ academic achievement and commitment. This dissertation attempts to bridge that gap by …

A Data Driven Model To Promote Preparedness And Respond Intelligently To Pandemic Outbreaks, Safea Mohammed Al Senani

Theses

The COVID-19 pandemic has had a major effect on various vital sectors of the economy, including education healthcare, and the industry. Governments have imposed strict regulations to reduce the spread of this global disease outbreak. Consequently, working from home, online learning, social distancing and various control measures were enforced. In response, many schools shifted to distance learning, although most of these schools were neither technically ready nor administratively prepared for the online transition. Despite recent progress, countries are still experiencing daunting challenges to control the infection rate and magnitude, stabilize the economy, and relax socialization and public life activities. Decision-makers …

The Effect Of Using The Gamification Strategy On Academic Achievement And Motivation Towards Learning Problem-Solving Skills In Computer And Information Technology Course Among Tenth Grade Female Students, Mazyunah Almutairi, Prof. Ahmad Almassaad

International Journal for Research in Education

Abstract

This study aimed to identify the effect of using the gamification strategy on academic achievement and motivation towards learning problem-solving skills in computer and information technology course. A quasi-experimental method was adopted. The study population included tenth-grade female students in Al-Badi’ah schools in Riyadh. The sample consisted of 54 students divided into two equal groups: control group and experimental group. The study tools comprised an achievement test and the motivation scale. The results showed that there were statistically significant differences between the two groups in the academic achievement test in favor of the experimental group, with a large effect …

A Reinforcement Learning Approach To Vehicle Path Optimization In Urban Environments, Shamsa Abdulla Al Hassani

Theses

Road traffic management in metropolitan cities and urban areas, in general, is an important component of Intelligent Transportation Systems (ITS). With the increasing number of world population and vehicles, a dramatic increase in road traffic is expected to put pressure on the transportation infrastructure. Therefore, there is a pressing need to devise new ways to optimize the traffic flow in order to accommodate the growing needs of transportation systems. This work proposes to use an Artificial Intelligent (AI) method based on reinforcement learning techniques for computing near-optimal vehicle itineraries applied to Vehicular Ad-hoc Networks (VANETs). These itineraries are optimized based …

Heart Rhythm Classification From Static And Ecg Time-Series Data Using Hybrid Multimodal Deep Learning, Ahmad Abdulrazaq Abdulla Alnajjar

Theses

Cardiovascular arrhythmia diseases are considered as the most common diseases that cause death around the world. Abnormal arrhythmia diseases can be identified by analyzing heart rhythm using an electrocardiogram (ECG). However, this analysis is done manually by cardiologists, which may be subjective and susceptible to different cardiologist observations and experiences, as well as to noise and irregularities in those signals. This can lead to misdiagnosis. Motivated by this challenge, an automated heart rhythm diagnosis approach from ECG signals using Deep Learning has been proposed. In order to achieve this goal, three research problems have been addressed. First, recognize the role …

Migrating From Sql To Nosql Database: Practices And Analysis, Fatima Jamal Al Shekh Yassin

Accounting Dissertations

Most of the enterprises that are dealing with big data are moving towards using

NoSQL data structures to represent data. Converting existing SQL structures to

NoSQL structure is a very important task where we should guarantee both better

Performance and accurate data. The main objective of this thesis is to highlight the

most suitable NoSQL structure to migrate from relational Database in terms of high

performance in reading data. Different combinations of NoSQL structures have been tested and compared with SQL structure to be able to conclude the best design to use.For SQL structure, we used the MySQL data that …

Integration Of Lightweight & Energy Efficient Cipher In Wireless Body Area Network Fore-Health Monitoring, Azza Zayed Aishamsi

Theses

There is an increase in the diseases of the circulatory system in United Arab Emirates, which makes it the first leading cause of death. This led to a high demand for a continuous care that can be achieved by adopting an emerging technology of e- Health monitoring system using Wireless Body Area Network (WBAN) that can collect patient’s data. Since patient’s data is private, securing the communication within WBAN becomes highly essential. In this research thesis, we propose an architecture to secure the data transmission within the Wireless Body Area Network (WBAN) in e-Health monitoring. More specifically, our proposed architecture …

Uav-Cloud: A Platform For Uav Resources And Services On The Cloud, Sara Yousif Mohamed Mahmoud

Theses

UAVs - Unmanned Aerial Vehicles – have gained significant attention recently, due to the increasingly growing range of applications. However, developing collaborative UAV applications using traditional technologies in a tightly coupled design requires a great deal of development effort, time, and budget especially for heterogeneous UAVs. Moreover, monitoring and accessing UAV resources using traditional communication media suffer from several restrictions and limitations. This research aims to simplify the efforts, reduce the time, and lower the costs of developing collaborative applications for distributed heterogeneous UAVs. In addition, the research aims to provide ubiquitous UAV resources access. A platform is proposed for …

Formal Specification And Refinement Of The Navigation Tasks Of Autonomous Robots, Eman Rabiah

Theses

Autonomous robots are hybrid systems whose role in our daily life is becoming increasingly critical. They are tasked with various activities requiring reliability, safety, and correctness of their software-controlled behavior. Formal methods have been proved effective in addressing development issues associated with these software qualities. However, even though autonomous robot navigation is a primordial function, there is no research dealing with enhancing reliability of the navigation algorithms. Thus, our focus is to investigate this type of algorithms, and specifically path planning, a fundamental and critical functionality supporting autonomy. We formally address the issue of enhancing reliability of the widely-used A* …