Digital Commons Network^™

Performance Analysis Of Underground-To-Aboveground Communication In Agricultural Iot Networks, Irfana Ilyas Manzil

Theses

This thesis investigates the potential of LoRa, a low-power, wide-area networking technology, for establishing reliable communication between underground sensors and aboveground infrastructure. We comprehensively analyze LoRa's performance in both single-hop and multi-hop configurations, considering the impact of diverse environmental factors such as soil composition, moisture content, underground transmission distance, and path loss on signal propagation. We delve into the crucial role of the spreading factor (SF) within the LoRa communication system, analyzing its influence on network performance. Furthermore, we develop a comprehensive mathematical model for bit error rate (BER) under various channel conditions, including additive white Gaussian noise (AWGN) and …

Fish-Eye Camera-Based Real-Time Pedestrian Crossing Predicting System, Mohammed Abdulla Almesafri

Theses

Fisheye cameras are widely used in traffic monitoring for their broad view, yet their distortion challenges deep-learning models in pedestrian detection and tracking. Despite available datasets like FishEye8K, collected in Hsinchu, Taiwan, and the availability of several studies that have delved into pedestrian prediction systems, a notable gap remains: the absence of datasets specifically designed for the cultural context of the UAE. This study aims to address this gap by introducing an in-house fisheye dataset tailored to enhance the prediction and tracking of pedestrians in fisheye footage within the UAE's environment. The present study addresses the development of a Graphical …

Exploring Emirati High School Students' Attitude Towards Reading In L2 (English), Seba Dabik

Theses

Reading in a second language (L2) is a crucial skill for high school students as it helps to develop their second language proficiency and broadens their understanding of the world. It also holds substantial significance in both their personal and academic endeavors. Additionally, proficient L2 reading skills pave the way for promising prospects and professional opportunities. This study examines students' attitudes towards reading academically and recreationally in L2 and the factors that contribute to these attitudes. The study sample comprised of 20 grade 11 UAE national male students (16-17 years old) enrolled in a public Applied Technology School (ATS) in …

Functional Characterization Of Potato Arp1 Gene Encoding Auxin-Repressed Protein, Sara Ali Alneyadi

Theses

Auxin-repressed proteins (ARPs) are conserved in higher plants and are involved in plant growth and development by controlling gene expression. ARP1 has been studied for its role in biotic stress response, but its role in abiotic stress response remains unclear. In this study, transgenic Arabidopsis plants expressing potato (S. tuberosum) ARP1 were evaluated for their salinity stress response. By gradually increasing NaCl concentrations from 0 to 200mM, plants were subjected to high salinity stress. As compared to wild-type (WT) control plants under stressed conditions, the ARP1 transgenic plants demonstrated improved height and root length and higher chlorophyll content. Under …

Clonality And Epidemiological Studies Of E. Coli Strain Collected From Abu Dhabi Emirate Using Ngs And Bioinformatic Tools, Ahmed Abdelrahman Mohamed

Theses

In the current landscape, where antibiotic resistance in bacteria is steadily rising, the role of bacterial genomics has assumed increasing significance. Therefore, it is necessary for microbiologists to acquire proficiency in the utilization of these methods and tools to harness their potential in gaining valuable insights into bacterial genomes. This can facilitate the development of innovative strategies for managing and treating bacterial infections. Here we present the power of the whole-genome sequencing technology in characterization of multidrug resistant Escherichia coli isolates. Fourteen Escherichia coli isolates were selected for this study. Following the standard microbiological techniques to confirm the sample identification, …

Topological Indices And Their Applications In Designing Drugs, Fedaa Ismail Abunawa

Theses

This research delves into the use of indices, in the field of drug design with a specific focus on anticancer medications. Topological indices, values derived from representations of chemical structures provide meaningful connections to the physical and chemical characteristics of molecules. These Indices act as tools for predicting behavior playing a vital role in crafting therapeutic drugs. The study primarily delves into topological indices like the Sombor index, Randi´c index, and Atom Bond Connectivity (ABC) index, which are calculated for structures and their relationships with physical properties such as molar volume, refractive index, and flash point are explored using statistical …

Cellular Automata Modeling Approach Of Addiction, Ruba Hameed

Theses

The purpose of this thesis includes the application of a mathematical model, as well as cell automata simulation, to shed light on the behavior of addiction spread in a population. The model describes the key determinants of drug addiction which includes peer influence, availability of substances, support networks, and awareness campaigns. The research aims to gain insights into the underlying mechanisms and patterns of addiction spread to develop effective prevention and intervention strategies.

The study begins by creating a discrete dynamical system that captures the transitions between 4 different states of substance use, including non-users (N), experimental users (E), recreational …

Technology-Enhanced Mathematics Teaching And Learning: Teachers’ Perspectives On Digital And Generative Ai–Enabled Tool Integration Through A Tpack Lens In Abu Dhabi Schools, Abdalrahman A. Adlouni

Theses

Digital learning is an active approach to education in daily life, and it has been implemented in all the schools in the United Arab Emirates (UAE). Many strategies, such as platforms, online educational websites, and other applications, were used by teachers to support blended learning and assist students in achieving their goals and accomplishing what is required from their curriculum. The main objective of this study is to examine teachers’ perceptions toward teaching mathematics using digital learning tools in Cycle 2 and Cycle 3. Data was collected from (n=114) mathematics teachers in Abu Dhabi City, UAE, during the spring semester …

Optimization Methods For Parameter Estimation In A Scalar Partial Differential Equation: Stochastic Variants, Yidan Yang

Theses

In this work, we present stochastic variants of an optimization method for the problem of recovering a spatially varying parameter in a scalar partial differential equation (PDE) from measurement(s) of the state variable. In many inverse problems associated with PDE models, the goal is to utilize observational measurements of the state variable in the estimation of the model parameter(s). In the problem being studied, the hydraulic conductivity of an aquifer (a function of location) is the parameter/coefficient to be recovered and the hydraulic (or piezometric) head is the quantity observed/measured. We discuss the choices of objective functional (such as output …

Models Of Rrna Templated Assembly Of The Nucleolus In The C. Elegans Embryo, Nishant Kodan

Theses

The nucleolus is a large membraneless organelle located in the nucleus of eukaryotic cells. It is a multicomponent structure primarily made of RNA and proteins and serves as the site of ribosome biogenesis. It has been extensively studied as a prototype of a membraneless organelle whose assembly is driven by phase separation, but factors affecting the dynamics of nucleolar assembly are not well understood. Experiments show that the size of the nucleolus scales with the size of the nucleus, which decreases through reductive divisions in the early C. elegans embryo. These observations are consistent with the idea that a finite …

Modeling The Reverberation Response Of The Broad Line Region In Active Galactic Nuclei, Sara A. Rosborough

Theses

The supermassive black holes (SMBHs) that reside at the centers of massive galaxies are observed as active galactic nuclei (AGN) when they are rapidly consuming matter from a surrounding accretion disk, which releases large amounts of electromagnetic radiation. Closely surrounding this engine are the dense gas clouds of the broad line region (BLR), which are photoionized by the continuum radiation emitted by the accretion disk. As these clouds are deep within the potential well of the SMBH, the gas emission lines (the broad emission lines; BELs) are Doppler-broadened by several 1,000 km/s. Measuring the size and velocity dispersion of the …

Neural Operator For Accelerating Coronal Magnetic Field Computations In Bifrost Mhd Model, Yutao Du

Theses

The application of the Tensorized Fourier Neural Operator (TFNO) to significantly enhance the computational efficiency of coronal magnetic field calculations within the Bifrost Magnetohydrodynamics (MHD) model is introduced in this study. Leveraging simulated data from the European Sunrise Science Data Center, the TFNO? an extension of the Fourier Neural Operator (FNO) that incorporates tensor decomposition for improved handling of high-dimensional data?is employed to solve time-varying partial differential equations (PDEs) over a 3D domain. The performance of the TFNO is compared with traditional machine learning methods, including Vision Transformer and CNN-RNN (encoder-decoder) architectures, to demonstrate its accuracy, computational efficiency, and scalability. …

Marking Estimation In Petri Nets Using Dynamic Mode Decomposition, Aditya Kale

Theses

Petri Nets (PNs) are a well-established framework for modeling and analyzing complex systems with interacting, concurrent processes. This thesis extends traditional Petri Net methodologies by integrating Dynamic Mode Decomposition (DMD), a technique originally developed for fluid dynamics, to analyze Continuous Petri Nets (CPNs). By applying DMD to CPN marking evolution, this research constructs a reduced-order model that captures its dynamics through dynamic modes and eigenvalues, enabling prediction of future markings without detailed knowledge of transition firings or underlying deterministic models. The principal contribution of this research is extending the kit of tools available for analysis of CPN dynamics, providing insights …

The Next Strike: Pioneering Forward-Thinking Attack Techniques With Rowhammer In Dram Technologies, Nakul Kochar

Theses

In the realm of DRAM technologies this study investigates RowHammer vulnerabilities in DDR4 DRAM memory across various manufacturers, employing advanced multi-sided fault injection techniques to impose attack strategies directly on physical memory rows. Our novel approach, diverging from traditional victim-focused methods, involves strategically allocating virtual memory rows to their physical counterparts for more potent attacks. These attacks, exploiting the inherent weaknesses in DRAM design, are capable of inducing bit flips in a controlled manner to undermine system integrity. We employed a strategy that compromised system integrity through a nuanced approach of targeting rows situated at a distance of two rows …

Comparison Of Methods For Creating Populations Of Models By Solving Stochastic Inverse Problems, Elizabeth Epstein

Theses

Given a parametric family of models and observational data, a researcher may be faced with an inverse problem: what distribution of parameters best creates a set of models that produce the observed data? Traditionally, Markov Chain Monte Carlo (MCMC) has commonly been used as a method to solve these stochastic inverse problems. In recent years, however, Generative Adversarial Networks (GANs) have been employed. The effectiveness of Markov Chain Monte Carlo methods as compared to a conditional generative adversarial network (cGAN) when applied to a family of models produced by a system of ordinary differential equations that model viral load over …

Tribological Performance Of Ceramic On Textured Polyethylene Contact For Artificial Hip Implants, Sandhya Vaidyanathan

Theses

Revision total hip arthroplasty (rTHA) is an expensive and surgically risky procedure that is necessary in the case of a failed primary total hip arthroplasty (pTHA). The cause of failure in artificial hip joints is often rooted in the tribological performance of the bearing surfaces such as increased wear and reduced lubrication. Surface texturing is a surface modification technique which has been studied for aerospace and automotive applications and has shown promise in the biomedical field of artificial human joints in the last two decades. Several studies have been done to assess the tribological performance of introducing surface micro-textures as …

Machine Learning Models For Enhanced Stock Trading Strategies, Alyaa Al Ali

Theses

The purpose of this research is to develop sophisticated machine-learning models that can predict stock price movements, taking into account the multifaceted influences that create volatility in financial markets. To navigate the complexities of market dynamics effectively, investors, financial institutions, and academia rely on precision stock price predictions. This research generates actionable buy and sell signals by using historical stock data, technical market indicators, Linear Support Vector Machines (LSVM), Neural Networks, and Logistic Regression. A distinctive feature of this model is it uses market indicators such as PPO, MACD, RSI Signal, Bollinger Bands, ROC Signal, and DX Signal instead of …

Unravelling Micro-Mysteries: Separating Microscopic Entities Using Electrokinetic Microsystems, Nuzhet Nihaar Nasir Ahamed

Theses

There is an increasing demand for the development of rapid and reliable methods for microparticle and cell separations in applications that range from clinical analysis to food and environmental safety assessments. Microfluidic systems, being portable and offering a response within minutes, are particularly attractive. Electrokinetic (EK) methods are a growing area in microfluidics, due to their robustness, rapid response time, low cost, and label-free analysis of micron-sized particles, including intact microorganisms. EK methods require the application of an electric stimulation, such as direct-current (DC) or alternating-current (AC) potentials, to induce different EK phenomena, such as electrophoresis, electroosmotic flow and/or dielectrophoresis, …

Spatiotemporal Alignment Of Event Stream With Images And Active Illumination, Abhijan Wasti

Theses

Unlike conventional frame-based cameras that form images by sampling all pixels within the duration of the global/rolling shutter, a pixel in an event camera can be triggered independently when the log intensity change in scene luminance at the pixel exceeds a threshold. This unique feature provides several advantages over conventional sensors, including high dynamic range (HDR) (≈120dB), high temporal rate (≈10,000Hz), low latency (< 1ms), and low power requirements (≈10mW). These properties make them excellent candidates for applications such as high-speed photography, HDR image reconstruction, object tracking, depth estimation, simultaneous localization and mapping, and surveillance and monitoring. Despite their potential, the asynchronous and spatially sparse nature of events poses challenges to event processing and interpretation. This is because most advanced image processing and computer vision algorithms are designed to work with conventional image formats, and not with temporally dense streams of asynchronous pixel events (i.e., the event stream). Although emerging techniques in supervised machine learning demonstrate promise, continued and rapid progress relies on the availability of labeled event datasets, which are scarce, and difficult to produce. Moreover, generating reliable events for training models is challenging due to the scene-dependent nature of event generation, which is further complicated by varying illumination and relative motion. In this thesis, we attempt to address these limitations with a novel imaging paradigm involving the capture of frames from a conventional frame-based camera that has been spa tially aligned and temporally synchronized with an event sensor. Our active illumination source allows us to generate events more consistently even under challenging illumination and motion in the scene. We demonstrate the feasibility of such a setup for a mobile eye tracking system and acquire subpixel and microsecond accurate spatiotemporal alignment. Our method facilitates the use of pre-trained models that operate on conventional images to detect features that can then be used to train models that can be applied directly to the event stream. This serves as the next step in event-based imaging and unlocks new possibilities in computer vision and imaging technology.

Exploring Microplastic Concentrations And The Sedimentology Of San Diego's Offshore Benthic Environments, Rachel Sarner

Theses

Marine pollution studies are showing infiltration of plastic debris in remote parts of oceans including the deep sea. Microplastics (MPs) are being discovered not only in the ocean’s water column but also benthic sediments reaching thousands of meters in depth. This is the first study to analyze MP concentrations in conjunction with sedimentary characteristics from varying deep-sea environments (coastal, deep ocean, offshore terrace) in the Southern California Continental Borderland (CCB). Our goal for this study was to observe how the concentration and type (morphology, color, size) of microplastics varied with distance from shore, with water depth, and between different submarine …

High Heat Flux Dissipation Techniques Using Enhancement Structures And Subcooled Boiling Chamber For High Performance Computing Applications, Maharshi Y. Shukla

Theses

With a rising need for high-performance computing in data centers, enhanced heat dissipation from microprocessors becomes critical for maintaining their surface temperature in a compact setting. While air cooling has been sufficient until now, liquid cooling proves to be superior in its heat dissipation capabilities. The present work investigates enhancing liquid cooling with boiling and enhanced boiling structures in a novel subcooled boiling chamber. The single-phase forced convection heat transfer is first studied by enhancing the heat transfer performance (CHF and HTC) by more than 50 % with the injection of air bubbles at the heater surface. A self-sustaining method …

Decentralisation Of Drone Authentication Within Iod Networks., Jarryd Tayler Brits

Theses

The applications of drones have become increasingly more versatile, with their popularity also increasing rapidly in the last decade. These applications span from entertainment within civilian markets to more military-based applications, including private security firms. However, with this rise in use, the security risks involved have also increased drastically, predominantly in a drone’s lack of ability to authenticate surrounding drones efficiently and securely without the aid of a third party. Although there have been copious amounts of research to support drone authentication, they predominantly rely on a single source of truth, such as a ground station server (GCS), which presents …

A Framework For Filtering Irrelevant Notams, Roudha Abdulrahman

Theses

The Notice to Airmen (NOTAM) system is essential for aviation safety, giving critical information on risks and operating limitations. However, the volume and complexity of NOTAM data complicate interpretation, which could compromise safety and efficiency. This study tries to address these issues by creating a predictive algorithm for analyzing NOTAM data and predicting whether to keep or remove them. The methodology combines effective machine learning algorithms to reveal insights that improve safety and operational efficiency. Using a dataset of NOTAM entries, multiple prediction algorithms are tested to forecast possible problems and enable proactive risk management. The study's findings help to …

Autowaze: Automated, Real-Time, And Accurate Traffic Analytics, Vijay Bajracharya

Theses

A key factor leading to the inefficiency of transportation systems is the lack of real-time, fine-grained traffic analytics. An average motorist in the United States spends a significant amount of time looking for parking spots during their daily commute. Existing systems for traffic analytics are either not scal- able to large metropolitan areas or require a human-in-the-loop. This project focuses on automating the detection of fine-grained traffic analytics. Lever- aging on-board stereo cameras, Autowaze utilizes a crowd-sourced strategy to take time-windowed snapshots of the road containing 3D map points of the environment. These snapshots are used to extract changes in …

On The Naming Of Identifiers: A Survey Of Undergraduate Students, Stacy Skalicky

Theses

Alsuhaibani et al. state that 60% of the participants do not have strict or any naming standards in the workplace and developers surveyed desired clear method naming standards to promote code comprehension [2]. Martin indi-cated identifier names are responsible for 90% of what makes software readable and understandable [25] . Borstler et al. indicated readability was important to developers at every level of experience but few report their academic influences being effectively leveraged to make quality identifiers [5]. Keuning et al. surveyed teachers in programming-related fields and found that code quality although important, was not a big part of their …

Electron Counting, Dopant Implementation, & Electron Phonon Interaction Mesh Sensitivity Testing For Nanoscale Energy Transport Model, Dominick Velez

Theses

Managing thermal energy generation and heat transfer within nanoscale devices (transistors) of modern-day electronics is important as it limits speed, carrier mobility, and affects device reliability. In the nanoscale, heat conduction occurs primarily via phonon transport and heat generation is a result of electron-phonon interactions in these devices. Traditional methods of predicting physical behavior have proven to lack either physical accuracy, computational efficiency, or flexibility. The Nanoscale Energy Transport Model (NETM) is an engineering design tool introduced to calculate non-equilibrium transport of energy carriers in nanoscale devices and overcome the deficiencies of traditional models of energy-carrier transport The NETM previously …

Computational Framework For Parameter Identification In The Nearly Incompressible Linear Elasticity System, Rachel Hawks

Theses

Breast cancer is one of the most common cancers in women and early detection is a key component in the treatment of cancer and can lead to drastic improvement of patient survival rates. Cancerous tissue is stiffer on average than healthy soft tissue, and in the presence of a compressive force, the stiffer areas tend to deform less than the softer areas. The problem being analyzed is based on a linear elasticity system that describes displacement in soft tissue under applied body forces in biomedical applications, specifically in the case of identifying soft tissue cancers. Elasticity imaging, or elastography, can …

Glacier Lake Inventory And Lake Outburst Flood Hazard Assessment In Kanchenjunga Conservation Area, Nepal, Prabish Khadka Chhetri

Theses

This study presents a comprehensive assessment of glacial lakes and land surface temperature (LST) dynamics within the Kanchenjunga Conservation Area (KCA) from 2010 to 2023. The KCA holds significant ecological importance, serving as a critical habitat for diverse flora and fauna, while also playing a vital role in regional hydrological systems. Additionally, its stunning landscapes attract tourists and mountaineers from around the world, further emphasizing the need for understanding environmental changes within the area. Utilizing medium to high-resolution satellite imagery from PlanetScope for glacial mapping and Landsat for LST analysis, the research aimed to achieve two primary objectives: creating an …

Second-Order Permutation Variable Importance: Quantifying And Attributing Uncertainty In Future Coastal Risk, Dwight Dinkins

Theses

Sensitivity analysis (SA) systematically assesses and quantifies a model’s uncertainty by examining the impact of parameter variations on the model’s output. An objective of sensitivity analysis is to ascertain model-input parameters that contribute the most to the uncertainty of a model’s output and could serve as a gauge to determine whether a parameter’s variation is suitable, expected, or a realistic representation of the phenomenon being modeled. Incorporating sensitivity analysis for assessing the importance of a model feature is imperative for decision-making. Therefore, as a statistical methodology, SA’s application in investigating coastal regions that are vulnerable to sea-level rise and extreme …

Color Change: Illumination And Observers, Che Shen

Theses

While color change is often associated with physical or chemical alterations in an object, this thesis focuses on perceptual color changes due to factors like color inconstancy under different lighting conditions, observer metamerism due to varying color matching functions, and individual differences in hue perception despite identical tristimulus values. Based on the complexities of color change phenomenon, a psychophysical experiment was conducted to establish the threshold of color inconstancy, where observers were tasked with categorizing colors under varying lighting. A major advancement in this thesis is the development of the Weighted Geometric Mean (WGM) model, an advanced chromatic adaptation model …