Physical Sciences and Mathematics 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 …

Electrical, Optical, And Thermal Properties Of Snse Based Materials With High Thermoelectric Performances, Najwa Qasem Al Bouzieh

Dissertations

This thesis conducts a thorough exploration of the characteristics and prospective applications of Tin Selenide (SnSe), a pivotal semiconductor for advancing contemporary electronics and optoelectronics. The investigation mainly focuses on comprehending the alterations in SnSe's properties when doped with elements such as Hafnium, Zinc, Bismuth, Germanium, Sodium, Iodine, and Silicon. 2D-SnSe allotropes, when doped with Hafnium, have exhibited remarkable optical characteristics, especially in the δ-SnSe allotrope, rendering it adaptable for varied optical uses like solar cells and LEDs. Additionally, evaluations of elasticity show improved resilience and augmented in-plane stiffness owing to Hf doping, occasionally reducing ductility. The work uniquely emphasizes …

First Principles Investigation Of Energy Harvesting Materials For Green Environment, Mehreen Javed

Dissertations

The cutting-edge research of materials enables the discovery of novel energy harvesting materials. In this project the structural, electronic, magnetic, thermodynamic, thermoelectric, and optical properties of different energy harvesting materials are studied. The main objective of this work is primarily to study thermoelectrically efficient half-heuslers and photovoltaically active perovskites. Variant schematics of innovative compounds with defect introduction are investigated. The compositionally altered compounds designed by introducing crystallographic defects in terms of substitutional or interstitial dopants, offer new trends of material properties. To accomplish the task, Density Functional theory based computational packages (VASP and Wein2K) are used. Using defect and strain …

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 …

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 …

Metal Oxide Based Materials For High Performance Supercapacitors, Hammad Mueen Arbi

Dissertations

Recent years have seen a healthy rise in the research and development of sustainable and renewable energy storage systems due to the pressing need to conserve natural resources and cut energy use. Due to the rapid growth in global population lately, there is a tremendous demand for energy to fulfill the ever-increasing needs. Innovative alternative energy sources and energy storage techniques are of tremendous interest for dealing with these current world issues. One promising solution for this is the recent research trend for achieving reliable and cost-effective high power and high energy density energy storage devices. On the basis of …

Ab-Initio Investigation Of 2d Materials For Gas Sensing, Energy Storage And Spintronic Applications, Saba Khan

Dissertations

The field of Two Dimensional (2D) materials has been extensively studied since their discovery in 2004, owing to their remarkable combination of properties. My thesis focuses on exploring novel 2D materials such as Graphene Nanoribbon (GNR), holey carbon nitride C₂N, and MXenes for energy storage, gas sensing, and spintronic applications, utilizing state-of-the-art techniques that combine Density Functional Theory (DFT) and Non-Equilibrium Greens Functions (NEGF) formalism; namely Vienna Ab-initio Simulation Package (VASP) and Atomistic Toolkit (ATK) package.
Firstly, on the side of gas sensing, the burning of fossil fuels raises the level of toxic gas and contributes to global …

Development Of Innovative Multi-Drug Approaches To Counteract Illicit Drug Abuse In The Uae Population, Manal Ali Alhefeiti

Dissertations

The abuse of addictive substances is on the rise in the United Arab Emirates (UAE) population. Consequently, the UAE government spends about Dhs 5.5 billion annually on the rehabilitation of drug addicts. Blood, urine, and hair tests can reveal signs of sporadic or chronic drug use. Given the list of banned chemicals in the UAE, our main objective in this work was to develop a novel analytical method to identify and measure banned substances, especially prescription and over-the-counter drugs in the UAE. We developed and validated a rapid, sensitive and reliable liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) approach for the targeted …

Lax Integrability And Solution Methods For The Nonlinear Schrödinger Equation With External Potentials: Exact Solutions And Applications, Laila Yahya Al Sakkaf

Dissertations

The investigation of a nonlinear differential equation (NLDE) integrability is the foundation for understanding and predicting the behavior of systems that are governed by that NLDE. The existence of a Lax pair (LP) representation is a reliable indicator of the indicator of the integrability of an NLDE. If an NLDE admits an LP, it is considered integrable in the LP sense, and this has important implications for the behavior and solutions of the system. The LP plays a crucial role in many powerful analytical solution methods for solving NLDEs. One such method is the Darboux transformation (DT), which allows for …

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 …

Diagnostics Of Dementia From Structural And Functional Markers Of Brain Atrophy With Machine Learning, Tetiana Habuza

Dissertations

Dementia is a condition in which higher mental functions are disrupted. It currently affects an estimated 57 million people throughout the world. A dementia diagnosis is difficult since neither anatomical indicators nor functional testing is currently sufficiently sensitive or specific. There remains a long list of outstanding issues that must be addressed. First, multimodal diagnosis has yet to be introduced into the early stages of dementia screening. Second, there is no accurate instrument for predicting the progression of pre-dementia. Third, non-invasive testing cannot be used to provide differential diagnoses. By creating ML models of normal and accelerated brain aging, we …

The Design, Synthesis, And Characterization Of Copper-Based Metal-Organic Frameworks For Their Investigation Against Cancer And Their Effect As Anti-Microbial Agents, Sandy Elmehrath

Dissertations

A wide range of nanomaterials have been developed for biomedical applications, such as drug delivery, biomedical imaging, and sensors. Nanomaterials can include nanoparticles (NPs) and nanofibers with various dimensions that are both natural and synthetic. A successful nanomaterial, for use in biological applications, is characterized by its biocompatibility, biodegradability, intrinsic high surfaces area, high interconnected porosity, and functionality. These features were achieved with the development of metal-organic framework (MOF) nanostructures. MOFs are assemblies of metal ions and organic linkers that are built into different geometries and can exist in all dimensions (up to 3-D). The choice of linkers with well-defined …

Soliton Based All-Optical Data Processing In Waveguides, Amaria Javed

Dissertations

The growing demand for higher data processing speed and capacity motivates the replacement of the current electronic data processing by optical data processing in analogy with the successful replacement of electronic data communication by optical data communication. In a quest to achieve comprehensive optical data processing we aim at using solitons in waveguide arrays to perform all-optical data processing operations. Solitons are special nonlinear waves appreciated for their ability to conserve their shape and velocity before and after scattering. They are observed naturally in diverse fields of science, namely, nonlinear physics, mathematics, hydrodynamics, biophysics, and quantum field theory, etc. with …

Development Of A Decision Support System For Sustainable Water Planning In Abu Dhabi, Uae, Mohamed Ibrahim Kizhisseri

Dissertations

One of the main challenges for water managers is to foresee the future accurately; then, design appropriate policies and infrastructure plans accordingly. The use of decision support systems in the field of water resource management and planning is now widely implemented, but its use in sustainable water planning of a nation or state in arid and semi-arid areas, such as Middle East countries, remains limited. The main objective of this dissertation is to present a graphical software tool that can assist water planners and decision-makers in long-term water management and planning. Sustainable planning for Abu Dhabi’s future water supply is …

Stochastic Delay Differential Equations With Applications In Ecology And Epidemics, Hebatallah Jamil Alsakaji

Dissertations

Mathematical modeling with delay differential equations (DDEs) is widely used for analysis and predictions in various areas of life sciences, such as population dynamics, epidemiology, immunology, physiology, and neural networks. The memory or time-delays, in these models, are related to the duration of certain hidden processes like the stages of the life cycle, the time between infection of a cell and the production of new viruses, the duration of the infectious period, the immune period, and so on. In ordinary differential equations (ODEs), the unknown state and its derivatives are evaluated at the same time instant. In DDEs, however, the …

Universal Constraints Of Kleinian Groups And Hyperbolic Geometry, Hala Alaqad

Dissertations

Recent advances in geometry have shown the wide application of hyperbolic geometry not only in Mathematics but also in real-world applications. As in two dimensions, it is now clear that most three-dimensional objects (configuration spaces and manifolds) are modelled on hyperbolic geometry. This point of view explains a great many things from large-scale cosmological phenomena, such as the shape of the universe, right down to the symmetries of groups and geometric objects, and various physical theories. Kleinian groups are basically discrete groups of isometries associated with tessellations of hyperbolic space. They form the fundamental groups of hyperbolic manifolds. Over the …

Assessment Of The Impact Of Climate Change On Land Use In The Emirate Of Abu Dhabi - An Environmental And Socio-Economic Perspective, Latifa Saeed Al Blooshi

Dissertations

This dissertation focuses on the impact of climate change on land use in the Emirate of Abu Dhabi – UAE. Climate change is a significant challenge resulting from natural and anthropogenic causes. Land use can stimulate changes in communities under climate change. The main objective of this dissertation is to assess the impact of climate change from an environmental and socio-economic perspective. In 2001, coastal sabkhas, mixed class and urbanized areas experienced an increase in temperature by (0.67, 1.14 and 1.16°C) respectively. In cities, urban areas are warmer than neighbouring rural areas. Unexpectedly, urbanization in desert areas in UAE led …

Activated Carbon Nanofibers From Renewable (Lignin) And Waste Resources (Recycled Pet) And Their Adsorption Capacity Of Refractory Sulfur Compounds From Fossil Fuels, Efstratios Svinterikos

Dissertations

Dementia is a condition in which higher mental functions are disrupted. It currently affects an estimated 57 million people throughout the world. Dementia diagnosis is difficult since neither anatomical indicator nor functional testing are currently sufficiently sensitive or specific. There remains a long list of outstanding issues that must be addressed. First, multimodal diagnosis has yet to be introduced into the early stages of dementia screening. Second, there is no accurate instrument for predicting the progression of pre-dementia. Third, non-invasive testing cannot be used to provide differential diagnoses. By creating ML models of normal and accelerated brain aging, we intend …

A Framework For Personalized Content Recommendations To Support Informal Learning In Massively Diverse Information Wikis, Heba M Ismail

Dissertations

Personalization has proved to achieve better learning outcomes by adapting to specific learners’ needs, interests, and/or preferences. Traditionally, most personalized learning software systems focused on formal learning. However, learning personalization is not only desirable for formal learning, it is also required for informal learning, which is self-directed, does not follow a specified curriculum, and does not lead to formal qualifications. Wikis among other informal learning platforms are found to attract an increasing attention for informal learning, especially Wikipedia. The nature of wikis enables learners to freely navigate the learning environment and independently construct knowledge without being forced to follow a …

Streaming Feature Grouping And Selection (Sfgs) For Big Data Classification, Noura Helal Hamad Al Nuaimi

Dissertations

Real-time data has always been an essential element for organizations when the quickness of data delivery is critical to their businesses. Today, organizations understand the importance of real-time data analysis to maintain benefits from their generated data. Real-time data analysis is also known as real-time analytics, streaming analytics, real-time streaming analytics, and event processing. Stream processing is the key to getting results in real-time. It allows us to process the data stream in real-time as it arrives. The concept of streaming data means the data are generated dynamically, and the full stream is unknown or even infinite. This data becomes …

Geochemical And Radiological Baseline Studies And Environmental Impact Of The Area Surrounding Barakah Nuclear Power Plant, Uae, Mouza Rashed Mohamed Al Rashdi

Dissertations

Geochemical, mineralogical and natural radiation analysis techniques were used for establishment of geochemical and radiological baseline around Barakah Nuclear Power Plant, UAE. The natural radioactivity concentrations of ²³⁸U (²²⁶Ra), ²³²Th and ⁴⁰K were measured for soil, shore and bottom sediment samples, using gamma spectrometry equipped with HPGe detector. In addition, alpha spectrometry was used to measure ²³⁴U/²³⁸U ratio for some selected samples. Furthermore, inductively coupled plasma atomic emission spectroscopy was used to measure the concentrations of heavy metals and Rare Earth Elements (REE). The grain size of the samples ranged from fine …

Cognitive Big Data Analytics And Persuasive Social Influence Diffusion, Eman Ahmed Ghanim Abukhousa

Dissertations

Current demands in local and global economies and the pursuit of competitiveness are calling for data-driven strategies. Data-driven solutions analyze trends, make predictions about future events, and prescribe what to do next in an actionable manner. However, cognitive and behavioral data are distinguished by their multiplicity and rapid changes to meet evolving and dynamic goals of individuals. This research work is concerned with the utility of analytical solutions to synthesize and influence cognitive and behavioral adoption. We propose a multidimensional data model to identify and extract cognitive indicators for analysis and persuasive interventions. The process starts by discovering behavioral features …

Mining Biological Networks Towards Protein Complex Detection And Gene-Disease Association, Eileen Marie Hanna

Dissertations

Large amounts of biological data are continuously generated nowadays, thanks to the advancements of high-throughput experimental techniques. Mining valuable knowledge from such data still motivates the design of suitable computational methods, to complement the experimental work which is often bound by considerable time and cost requirements. Protein complexes or groups of interacting proteins, are key players in most cellular events. The identification of complexes not only allows to better understand normal biological processes but also to uncover Disease-triggering malfunctions. Ultimately, findings in this research branch can highly enhance the design of effective medical treatments. The aim of this research is …

Protein Domain Linker Prediction: A Direction For Detecting Protein-Protein Interactions, Maad Mohammad Hasan Shatnawi

Dissertations

Protein chains are generally long and consist of multiple domains. Domains are the basic elements of protein structures that can exist, evolve, and function independently. The accurate and reliable identification of protein domains and their interactions has very important impacts in several protein research areas. The accurate prediction of protein domains is a fundamental stage in both experimental and computational proteomics. The knowledge of domains is an initial stage of protein tertiary structure prediction which can give insight into the way in which proteins work. The knowledge of domains is also useful in classifying proteins, understanding their structures, functions and …

Scalable Multi-Hop Data Dissemination In Vehicular Ad Hoc Networks, Moumena Abdullah Chaqfeh

Dissertations

Vehicular Ad hoc Networks (VANETs) aim at improving road safety and travel comfort, by providing self-organizing environments to disseminate traffic data, without requiring fixed infrastructure or centralized administration. Since traffic data is of public interest and usually benefit a group of users rather than a specific individual, it is more appropriate to rely on broadcasting for data dissemination in VANETs. However, broadcasting under dense networks suffers from high percentage of data redundancy that wastes the limited radio channel bandwidth. Moreover, packet collisions may lead to the broadcast storm problem when large number of vehicles in the same vicinity rebroadcast nearly …

Natural Radioactivity In Groundwater, Rocks And Sediments From Some Areas In The Uae: Distribution, Sources And Environmental Impact, Dalal Matar Al Shamsi

Dissertations

Groundwater contains a certain amount of natural radioactivity that generally results from the decay of uranium, thorium and 40K isotopes. Knowledge of concentration levels, spatial distribution and sources of these isotopes in groundwater is crucial for environmentally safe and sustainable groundwater resources in the United Arab Emirates (UAE). This dissertation focuses on investigating the distribution, environmental impact and sources of 235U, 238U, 232Th, as well as the activity of gross β and α in groundwater in some locations in the UAE. Additionally, groundwater samples from Oman and selected aquifer rocks and sediments from the UAE were analyzed for comparison. A …

Community Detection And Influence Maximization In Online Social Networks, Kanna Gharib Al-Falahi

Dissertations

The detecting and clustering of data and users into communities on the social web are important and complex issues in order to develop smart marketing models in changing and evolving social ecosystems. These marketing models are created by individual decision to purchase a product and are influenced by friends and acquaintances. This leads to novel marketing models, which view users as members of online social network communities, rather than the traditional view of marketing to individuals. This thesis starts by examining models that detect communities in online social networks. Then an enhanced approach to detect community which clusters similar nodes …

Management Of Dairy Farm Wastewater – A Case Study, Saed Mohamed Al Awadi

Dissertations

There are several dairy farms and milk processing plants in U.A.E. which contribute to the problem of industrial wastewater discharges in the country. This study emphasized the waste management aspects of dairy farms and examined the wastewater characteristics, wastewater treatment and effluent reuse in Al-Rawabi Dairy Plant in Dubai as a case study.

An extensive sampling and analysis program was conducted over a period of one year to determine wastewater characteristics at Al-Rawabi Dairy Plant. It has been found that the wastewater COD, BOD, Solids, Nitrogen and Phosphorus content is relatively high but daily variations in pollution loads were not …