Digital Commons Network^™

Analysis Of Cycle 2 Science Textbooks For Representation Of Elements Contributing To Quality Science Textbooks As Learning Resources, Sohani Mehzabin Prova

Theses

Science textbooks are a valuable resource for both students and teachers. They hold a significant role in students' learning of science. Most science teachers in the United Arab Emirates (UAE) rely on science textbooks as the foundation for their teaching. However, until now, limited research has been conducted to assess the appropriateness of science textbooks prescribed by the Ministry of Education in the UAE. Therefore, this study aims to evaluate the representation of elements contributing to the suitability of cycle 2 (grades 5 to 8) science textbooks as learning resources as prescribed by the Ministry of Education of the UAE. …

Modification Of Cellulose Fibers By Acyl Grafting For Oil Spill Remediation, Fatima Saif Alhumaidi

Theses

Oil spills represent a significant source of aquatic pollution with substantial repercussions on the environment as well as the economic and societal well-being of coastal communities. This research project is focused on the utilization of chemically modified cellulose-based fibers to remediate oil-contaminated water. The hydroxyl groups present in cellulose were acetylated under optimized conditions, thereby rendering the fibers hydrophobic and enhancing their affinity for crude oil. The modified cellulosic material was characterized by several physical and chemical techniques (IR, TGA, contact angle measurement, SEM, and back titration) to determine the extent of acylation and assess their morphological properties. The derivatized …

Commissioning Of The Uaeu Radio Array And Pilot Low-Frequency Radio Astronomy Studies, Aisha Ali Alnaqbi

Theses

As part of the UAEU Radio Astronomy Pathway Project, a 256-element Ground based Radio Array Facility was deployed at the UAEU. A comprehensive exploration of radio astronomy, and investigations on existing radio arrays, emphasizing low-frequency radio signals and the challenges faced at this range, are crucial for the commissioning phase of the array. A core aspect discussed is the vital role of coaxial cables in preserving the integrity of low-frequency radio signals. To address the electrical length differences between the coaxial cable pairs used to connect the array’s beamformers in the field to the beamformer controllers in the control room, …

Ai Application In Architecture In Uae: Developing And Testing Advanced Optimization Model For A Parametric Shading Structure As A Retrofit Strategy Of A Midrise Residential Building Façade In Downtown Abu Dhabi, Anwar Ghaleb Ahmad

Theses

Artificial intelligence is a phenomenon that influences every aspect of our lives. AI applications have already started to change the methods in different disciplines. Architecture is one of the disciplines that is highly affected by the developments of AI technologies. With the United Arab Emirates heading to employ new technology to lead the country and region development, it is important to explore and develop the application of AI in the strategic disciplines of the country in which the built environment is essential. This study aimed to develop and evaluate an advanced model script (to be used as a tool) using …

Impact Of Covid-19 On Security Vulnerabilities Of Learning Management Systems: A Study Towards Security And Sustainability Enhancement, Souheil Abdel-Latif Akacha

Theses

The rapid adoption of Learning Management Systems (LMSs) like Moodle, Chamilo, and Ilias became essential for online education due to the Coronavirus Disease 2019 (COVID-19) pandemic, revolutionizing online learning while exposing security vulnerabilities. This thesis explores security concerns within these LMSs across different pandemic periods. By analyzing existing patches, security measures, and emerging cybersecurity technologies, recommendations are formulated to enhance LMS security against evolving cyber threats, providing actionable insights for educational institutions to ensure secure online education continuity. The numerical findings highlight the increasing need for proactive security measures in Moodle, the fluctuating nature of vulnerabilities in Chamilo, and the …

Radio Emission From Low Mass Active Galactic Nuclei, Ammara Aftab

Theses

Massive black holes of a few million to billion solar masses lurk at the centers of the most present-day massive galaxies but their origin is still unknown. The low mass galaxies (M* ~ 3x10⁹ Mʘ) hosting black holes with masses ranging from 10³ to 10⁵ Mʘ are ideal laboratories to test the models of black hole formation and they may help in understanding the co-evolution of central black holes with their host galaxies. In this thesis, we have developed a detailed theoretical model/framework to estimate the radio emission from low-mass active galactic nuclei (AGN). We also compute …

Radio Emission From Low-Mass Active Galactic Nuclei, Ammara Aftab

Theses

Massive black holes of a few million to billion solar masses lurk at the centers of the most present-day massive galaxies but their origin is still unknown. The low mass galaxies (M* ~ 3x10⁹ Mʘ ) hosting black holes with masses ranging from 10³ to 10⁵ Mʘ are ideal laboratories to test the models of black hole formation and they may help in understanding the co-evolution of central black holes with their host galaxies. In this thesis, we have developed a detailed theoretical model/framework to estimate the radio emission from low-mass active galactic nuclei (AGN). We also …

Estimating Mars Surface Wind Stress And Dust Lifting Using Reanalyses Based On Emm And Other Spacecraft Observations, Haneen Abouhaligah

Theses

Studying Mars offers insights into terrestrial planet evolution and informs future human expeditions. This thesis examines dust dynamics in Mars’ lower atmosphere, focusing on understanding its weather and climate. We investigate the role of Near-Surface Wind Stress (NSWS) in dust lifting, using six reanalysis datasets, respectively: MACDA, EMARS, OpenMARS, ACS–TIRVIM (ExoMars observations of the MY34 Global Dust storm), EMM1 and EMM2. Following the parameterization approach by Newman et al. (2002a), areas of agreement and discrepancy among datasets were identified. Time series analysis revealed consistent results where datasets overlap temporally. Some differences were expected and shown due to the different Global …

Learning To Learn From Sparse User Interactions, Krishna Prasad Neupane

Theses

The ability to learn from user interactions provides an effective means to understand user intent through their behaviors that is instrumental to improve user engagement, incorporate user feedback, and gauge user satisfaction. By leveraging important cues embedded in such interactions, a learning system can collect key evidence to uncover users’ cognitive, affective, and behavioral factors, all of which are critical to maintain and/or increase its user base. However, in practical settings, interactive systems are still challenged by sparse user interactions that are also dynamic, noisy, and highly heterogeneous. As a result, both traditional statistical learning methods and contemporary deep neural …

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 …

Investigation And Analysis Of Circular Economy Indicators In The Manufacturing Industry, Dina Al Jamal

Theses

In the pursuit of sustainable development, the concept of the Circular Economy (CE) has emerged as a compelling and transformative alternative to the traditional linear economic model (i.e., take, make, use, dispose). The limitations of the linear economy in addressing contemporary global challenges have highlighted the urgency of adopting a more regenerative approach. Simply put, the circular economy aims to maximize the value extracted from available resources over their lifecycle, thereby ensuring the fulfillment of both current and future generations' needs. This thesis sheds light on a pivotal solution for effectively integrating circular economy principles into enterprises, thereby reinforcing sustainability. …

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 …

Predicting Payment Defaults In Customs Authorities, Ahmed Fayed Elnahel

Theses

As the global economy continues to expand, international trade is growing at an unprecedented rate, resulting in a surge of cargo movements across borders. With so much activity taking place, it's imperative that customs systems operate intelligently to identify potential risks in every transaction and highlight any potential fraud or manipulation that may be occurring. Customs play a crucial role in supporting legitimate trade, protecting society, and promoting sustainable economic development. However, it is unfortunate that some companies take advantage of the facilities provided by customs departments to avoid paying their duties or engaging in smuggling from the free zone …

Equilibrium And Active Self-Assembly And Collective Properties Of Network-Based Biomaterials, Lauren Melcher

Theses

Biological systems have the unique ability to self-organize, respond to environmental stimuli, and generate autonomous motion and work. The fields of biomaterials and synthetic biology seek to recapitulate these remarkable properties of biological systems in in-vitro reconstitutions of biological systems, and in abiotic or biotic-abiotic hybrid materials to better understand the underlying rules of life and to predict the design principles of biomimetic smart materials. Motivated by this, we create bottom-up mathematical models, rooted in experiments, of network-based synthetic and biological materials. These encompass two-dimensional colloidal networks connected by rhythmic crosslinkers, and three-dimensional biopolymer networks assembled via depletion interactions, physical …

What Is The Best Way To Develop A Website?, Nahomy Julieta Calderon Lopez

Theses

This project is centered around empowering individuals with the knowledge and resources necessary for effective website development. The culmination of Thesis/Directed Project II is a user-friendly website designed to distill and present the insights gathered during Thesis/Directed Project I. This website features an engaging interactive quiz, aimed to help the users identify what is the best way, for them, to develop a website. The quiz has multiple questions, each with three distinct response options, the quiz guides users towards one of three key approaches for website development: Website Builders, Content Management System platforms, or Coding. Upon receiving their quiz results, …

A Numerical Investigation Realizing The Flow Structure And Heat Transfer Performance Of The Potential Impinging Jets, Mohammed Sami Uddin Khan

Theses

The demand for improvement in the performance of gas turbines has led to the consideration of flows at increasingly high temperatures, but this introduces challenges in terms of maintaining their structural integrity and preventing overheating. To respond to these challenges, gas turbine manufacturers have turned to internal cooling, and jet impingement provides an effective solution for cooling the leading edge of the blades of gas turbines. In this study, the author numerically simulated the cooling performance of the leading edge of the blades of a gas turbine under constant heat flux by using five configurations of jet impingement: a steady …

Robust Weakly Supervised Learning For Real-World Anomaly Detection, Hitesh Sapkota

Theses

Anomaly detection has attracted increasing attentions from diverse domains, including medicine, public safety, and military operations. Despite its wide applicability, anomaly detection is inherently challenging as abnormal activities are usually rare and unbounded in nature. This makes it difficult and expensive to identify all potential anomalous events and label them during the training phase so that a detection model can provide robust prediction on unseen event data. Unsupervised and semi-supervised learning models have been explored, which achieve a decent detection performance with no or much less annotations. However, these models can be highly sensitive to outliers (\ie normal samples that …

Graph-Based Learning Networks For Automatic Pigment Mapping Of Historical Artifacts, Bei Cao

Theses

Hyperspectral image classification can be a difficult task due to a lack of ground-truth labels and spectral variability. For hyperspectral images (HSIs) of historical artifacts, which are generally man-made objects, this is generally a significant challenge. Aiming to differentiate subtle spectral differences between varied pigments, we introduce graph- based learning networks and a powerful learning pipeline for realizing automatic pigment mapping on the maps. First, we develop a Graph Modularity clustering method for pro- ducing trustworthy ground-truth map for pigment classification task. We analyze the influence of graph structure on the Graph Neural Networks and propose Spatial-Spectral Graph Convolutional Network …

Optimization Of Alternative Mask Absorber Materials For Euv Lithography, Rajiv Naresh Sejpal

Theses

In efforts to continuously scale feature dimensions in semiconductor manufacturing, the industry has moved from refractive optical lithography to reflective extreme ultra-violet lithography (EUVL). The latter provides a significant improvement in the resolution by illuminating mask patterns using 13.5nm source wavelength at oblique chief ray angles (CRA). A typical EUVL mask consists of a multilayer Bragg mirror topped with a 55-70nm Tantalum-based (Ta-based) absorber stack to obtain layout patterns. This current three-dimensional (3D) mask architecture in combination with a small source wavelength and oblique illumination angles results in mask 3D (M3D) effects such light shadowing, pitch dependent best focus variations, …

Spherical Harmonic Analysis And Filtering Of Weyl Scalar Ψ4, Jackson Bates

Theses

Numerical Relativity simulations play an important role in the Astrophysics community through their ability to create templates and test specific solutions to Einstein’s Field Equations. As Gravitational Wave Astronomy has grown over the past decades, the need for accurate and efficient codes has grown as well. Binary Black Hole Merger simulations provide the template needed by modern Gravitational Wave Detectors (LIGO/Virgo) to verify the integrity of detected symbols.

Improvement of these merger simulations aids both the experimental and numerical sides of physics, as well as verifying the theoretical side. A major issue that arises from any numerical simulation of a …

Deep Reinforcement Learning And Hybrid Approaches To Solve Multi-Vehicle Combinatorial Optimization Problems, Prashant Sankaran

Theses

Combinatorial optimization problems are an important class of problems often encountered in the real world involving a combinatorially growing set of feasible solutions as the problem size increases. Since exact approaches can be computationally expensive, practitioners often use approximate approaches such as metaheuristics. However, sophisticated approximate methods that yield high-quality solutions require expert help to handcraft or fine-tune the solution process to suit a given problem distribution. In recent years, artificial intelligence (AI) approaches that involve learning from data without being explicitly programmed have shown tremendous success at various challenging tasks, like natural language processing and autonomous driving. Therefore, solving …

Analyzing The Impact Of Process-Oriented Technology In Programming Education, Kate Arendes

Theses

Currently, there exist several factors in programming education that deter novice programmers. Computer science students are often significantly penalized for programs that do not compile, reflecting how current teaching standards are focused on the product of the student’s efforts, rather than the independent pieces of code that would otherwise execute properly. Novice programmers struggle with interpreting error messages that identify where and why a program failed, but are written with the assumption that the author already has mastered the fundamental concepts that they are trying to implement. In the classroom, educators may show presentations with pre-written code or perform live …

3d Computational Modeling Of Multiphase Phenomena In Boiling Heat Transfer, Winston O. James Iii

Theses

Boiling heat transfer is used in industrial processes, such as heat exchangers, nuclear reactors, and high-powered electronics. There is a need to generate effective heat dissipation techniques to increase the operation limits of these technologies. To enhance heat dissipation with boiling flows, it is important to study boiling phenomena from a fundamental perspective to identify the relation between the fluid and heat transfer behavior near the interface during bubble growth. Boiling simulations have been used as a tool to visualize and quantify the heat transfer mechanisms near the interface. However, challenges exist in modeling bubble growth with a sharp interface …

Population Inference Of Non-Spinning Eccentric Binary Black Holes, Muhammad Zeeshan

Theses

Compact binary mergers produce gravitational waves (GWs), which carry information about their sources. The LIGO-VIRGO-KAGRA network detects GWs signals, and we use those measurements to infer BBHs population properties such as mass, spin, and eccentricity distribution in the universe. Binary component masses and spins are well-known to provide insight into the source formation, evolution, and environment. Unlike these two, eccentricity is a unique and measurable signature of strongly interacting events. Unfortunately, most available parameter estimation results for GWs signals do not include eccentricity: models for binary merger with eccentricity have minimal availability and parameter coverage. Therefore, to assess how well …

Optimized Generative Pre-Training Eeg To Sentiment Classification (Ogptsc), Amira Hassan

Theses

This research aims to revolutionize electroencephalogram (EEG) analysis by proposing and developing an innovative method for sentiment classification, introducing the groundbreaking "Optimized Chat Generative Pre-training EEG to Sentiment Classification (OGPTSC)." This novel approach harnesses the power of Generative Pre-training (GPT2) as the vocabulary language model while utilizing an intelligent hyper-parameter selection method to fine-tune and optimize the model's performance. Extensive testing is conducted on a widely recognized dataset to evaluate the OGPTSC's prowess, demonstrating its exceptional capabilities in sentiment classification. Notably, this research extends its scrutiny beyond the OGPTSC by applying the same hyper-parameter selection technique to well-established models such …

Model-Free Sliding Mode Control In The Lateral And Direction Dynamics Of An Aircraft, Nicholas Hutson

Theses

Traditional control methods require extensive tuning or a derivation of a system model making them increasingly antiquated for use on new, more complex systems. Sliding Mode Control has emerged as a more effective alternative as a control method that can directly handle nonlinear systems with increased robustness while guaranteeing stability. However, it is still limited by the need for a system model for the derivation of the controller form. This work proposes a new model-free control method based on Sliding Mode Control referred to as Model-Free Sliding Mode Control where the form of the controller is only dependent on system …

Design Of A Current Mode Circuit For Zeroth-Order Optimization Of Memristor-Based Neuromorphic Systems, Shery George Mathews

Theses

Artificial neural networks (ANNs) have become widely used over the past decade due to their excellent performance in applications such as object recognition and classification, time series forecasting, machine translation, and more. Key factors contributing to the success of ANNs in these domains include the availability of large datasets and constant improvements in powerful parallel processing architectures such as graphics processing units (GPUs). However, modern ANN models' growing size and complexity preclude their deployment on resource-constrained hardware for edge applications. Neuromorphic computing seeks to address this challenge by using brain-inspired principles to co-design the ANN hardware and algorithms for improved …

Rare Earth Element Extraction From Secondary Source Materials: Understanding Economics And Environmental Impacts Of Development., Ajay Kumar Gupta

Theses

Rare earth elements are an integral part of modern industry. Although not “rare” in terms of crustal abundance, concentrations in natural deposits are rarely of economic benefit. Vital to high-tech sectors and sustainable technologies, such as renewable energy, electric transportation, military, and medicine, rare earths are traditionally produced with high environmental impact and complications of economic efficiency in separating 15 – 17 chemically similar metals that occur in tandem. Given the rapid growth projected for these metals, development is expected to increase around the globe and new deposits for rare earths is of interest. Recovering them from secondary sources, such …

Design And Optimization Of Devices And Architectures For Neuromorphic Silicon Photonics, Matthew Van Niekerk

Theses

Neuromorphic photonics is an exciting field at the intersection of neuroscience, integrated photonics, and microelectronics. To realize large-scale neural network-inspired systems, we must have a toolbox of linear and nonlinear operators. Here, we review state of the art for integrated photonic linear operators, which can perform linear operations using interference or wavelength-division-multiplexing (WDM) techniques, and nonlinear operators, which perform nonlinear operations with a combination of photodetection and modulation. We present some devices that fit into the needed toolbox. A new type of directional coupler, using skin depth engineering of electromagnetic waves, suppresses optical crosstalk and eliminates the need for waveguide …

Focus Calibration And Point Spread Function Analysis For The Cosmic Infrared Background Experiment-2, Mike Parra Ortiz

Theses

The Epoch of Reionization is the period in the evolution of the Universe that spans the birth of the first stars and galaxies. During this time early UV-bright galaxies ionized the neutral intergalactic medium, leaving an imprint on the extra-galactic background light (EBL). The Cosmic Infrared Background ExpeRiment (CIBER-1) was designed to measure the EBL in the near-infrared (NIR) at redshifts z > 6 to observe the signal from reionizing sources. CIBER-1 measured excess radiation at NIR wavelengths when compared to expectations. The Cosmic Infrared Background ExpeRiment-2 (CIBER-2) was designed to better constrain the excess radiation observed by CIBER-1. Having the …