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Modeling The Effects Of Shed Target Receptors On The Efficacy Of Cancer Immunotherapy Agents, Bridget M. Torsey
Modeling The Effects Of Shed Target Receptors On The Efficacy Of Cancer Immunotherapy Agents, Bridget M. Torsey
Theses
Cancer cells often shed receptors targeted by immunotherapies. Shed receptors can reduce drug efficacy by binding to free drug, preventing its binding to membrane-bound receptors. The goal of this dissertation is to investigate the effects of shed targets on the efficacy of cancer immunotherapies. First, we study liquid tumors by extending a PK/PD model to include receptor shedding, drug-induced enhancement of shedding, drug binding to shed receptors, and drug-induced tumor lysis. We use our model to elucidate the effect of shed target receptors on the efficacy of immunotherapies through uncertainty and sensitivity analyses. Our findings support the claim that the …
Rise Of Social Media Hacking: Ai-Based Ip Tracking For Uae Law Enforcement, Mounikha Naarrayen Chakravarthula
Rise Of Social Media Hacking: Ai-Based Ip Tracking For Uae Law Enforcement, Mounikha Naarrayen Chakravarthula
Theses
Social media has evolved into a critical channel for communication, expression, and public influence, but it has also become a prevalent avenue for cybercrime, particularly in digitally advanced nations such as the United Arab Emirates (UAE). The rising complexity of online offences, coupled with anonymisation tools and cross-border digital behaviour, has made the attribution of social-media-based cyber incidents increasingly challenging for law enforcement. In this context, artificial intelligence (AI) offers the potential to strengthen digital investigations by providing intelligent, scalable, and evidence-driven attribution capabilities. This research develops an AI-assisted Internet Protocol (IP) attribution framework tailored specifically for UAE law enforcement …
Adaptive Design Solutions For Golfers With Arm Impairment, Samuel Hao-Yu Wang
Adaptive Design Solutions For Golfers With Arm Impairment, Samuel Hao-Yu Wang
Theses
Golf is a game of precision, focus, and enjoyment for everyone, regardless of age, physical condition, or experience. However, for many people with disabilities, full participation in the game can be challenging. This project created an inclusive golfing experience for players with physical disabilities by assisting them with specific actions required in golf. The goal was to design solutions that reduce limitations caused by impairments, enabling players to enjoy the game with greater freedom. The United States Disabled Golf Association recognizes 14 sport classes of physical impairments, categorizing competitors by different types and levels of disability. This project focused on …
Predictive Modeling Of Tokenized Real Estate Prices Using Machine Learning, Mohammed Alteneiji
Predictive Modeling Of Tokenized Real Estate Prices Using Machine Learning, Mohammed Alteneiji
Theses
In this paper, we propose a machine learning-based model to predict the prices of tokenized real-estate assets, combining blockchain data, real-estate data, and sentiment data. Tokenization refers to partitioning a physical asset into fractional tokens on a blockchain, where each token represents a fraction of that asset. These include token liquidity, trading volume, platform activity, and the on-chain activity of investors. These new variables require data-based analytics that are capable of accounting for more complex relationships than customary real estate valuation approaches. To address this, we propose a multimodal dataset that incorporates on-chain data (token supply, number of wallet-holders, transaction …
Unmasking Corruption And Bribery Using Predictive Analytics, Maha Salem
Unmasking Corruption And Bribery Using Predictive Analytics, Maha Salem
Theses
The initiative (Unmasking Corruption and Bribery Using Predictive Analytics) aims to identify employees in government sectors who commit corruption and bribery by addressing issues such as the lack of transparency, fairness, equality, and public trust, as well as weakened loyalty and poor reputation. This project focuses on data analytics and predictive modeling to detect suspicious or high-risk employee behaviors related to corruption and bribery. The main objective is to reduce these unethical activities in government sectors, strengthen integrity, and promote transparency and public trust through predictive capabilities. It also seeks to raise awareness about how serious and harmful these crimes …
Comparative Analysis Of Machine Learning Models For Spam Email Detection, Rashed Almarri
Comparative Analysis Of Machine Learning Models For Spam Email Detection, Rashed Almarri
Theses
The current research examines one of the most effective approaches to spam email detection based on machine learning and natural language processing (NLP). The study is placed in the context of the rising cyber threats and the influx of emails, where the spam/ham data is to be classified correctfully using the combination of the Logistic Regression, NLP (including tokenization, lemmatization, and TF-IDF vectorization). The questions of the research were devoted to the efficiency of such an approach and the interpretation of its results. The data used are obtained by a publicly available Kaggle data set that contains 5,572 labeled email …
Data-Driven Crime Prediction: Toward Smarter Reduction Strategies, Zayed Almarri
Data-Driven Crime Prediction: Toward Smarter Reduction Strategies, Zayed Almarri
Theses
This study explores how machine learning and weather data can be used for the prediction of crime more accurately in the city of Seattle. Predictive policing is a method in law enforcement that uses data and computer algorithms to forecast the locations that crimes are likely to happen. Although many studies focused on using past crime data alone, this research also includes weather conditions like temperature, rainfall, and humidity, which may influence when and where crimes occur. Several machine learning models, including Random Forest (RF) and Support Vector Machines (SVM), were used to classify areas of the city into high-risk …
The Role Of Technology In Modernizing Prison Management Systems, Essa Anwahi
The Role Of Technology In Modernizing Prison Management Systems, Essa Anwahi
Theses
This thesis examines the role of technology in modernizing prison management systems and improving operational efficiency, security, and decision-making. It explores how digital technologies and data analytics can address challenges in traditional prison management, such as inefficient processes and limited data utilization. The study highlights the potential of technology-driven solutions to enhance system performance and support more effective management practices within correctional facilities.
Investigating The Effect Of Build Direction On Mechanical Properties In Pellet-Based 3d Printing, Yahya Mohammed
Investigating The Effect Of Build Direction On Mechanical Properties In Pellet-Based 3d Printing, Yahya Mohammed
Theses
This study investigates the influence of build orientation on the mechanical performance of Polylactic Acid (PLA) components fabricated using Fused Granular Fabrication (FGF), a pellet-based additive manufacturing method, and benchmarks these results against Fused Deposition Modeling (FDM). Although orientation-dependent mechanical behavior has been widely studied in filament-based extrusion, there remains a critical gap in understanding how these effects appeared in pellet-based fabrication. To address this gap, PLA tensile and compression specimens were fabricated using both FGF and FDM under identical geometries, processing parameters, and preparation procedures, ensuring that any differences in performance arise solely from the manufacturing method and build …
Achilles, Sreelekha Samala
Achilles, Sreelekha Samala
Theses
ACHILLES is a speculative design project and conceptual artifact. It is not intended to function as a medically certified or biomechanically operational prosthetic arm. Instead, it operates within the realm of design research, using visual realism and luxury aesthetics to explore how assistive technologies could be perceived differently in cultural, emotional, and commercial contexts. Using 3D software to experiment with color, pattern, and texture, I designed a realistic mockup to demonstrate how Achilles could appear in a high-end commercial setting. Instead of animating the model, I focused on camera motion to highlight the prosthetic from multiple angles, emphasizing its sculptural …
Early Electrical Fault Detection In Power Systems Using Data Analytics, Hessa Alraeesi
Early Electrical Fault Detection In Power Systems Using Data Analytics, Hessa Alraeesi
Theses
The increasing penetration of renewable energy, especially solar generation, has introduced higher variability into power system loading, making early detection of electrical faults more challenging yet more essential for maintaining network reliability. This research presents a machine-learning–based framework for early electrical fault detection using a Random Forest model developed in DataRobot. Due to confidentiality constraints on DEWA operational data, a Kaggle dataset was adopted and enriched with simulated solar irradiance variability to mirror real network conditions in the UAE. After comprehensive data preprocessing and feature engineering, the Random Forest model demonstrated strong generalization performance, accurately distinguishing early fault signatures from …
Mercurial, Bhavana Neti
Mercurial, Bhavana Neti
Theses
Mercurial is a groundbreaking visual journey through typography that charts the fluid and often volatile passage, from the depths of sadness, eventually finding the light in the end, inspired by the song title Louder than Bombs by BTS, a Korean boyband. Over a carefully observed period, this book captures the subtle and dramatic transformations of emotion through a unique lens. "Mercurial" represents a unique and multi-layered approach to understanding and visualizing emotions. Initially, the exploration of shapes as a representational tool proved inadequate for capturing this complexity. This led to a pivotal shift towards typography, where the inherent qualities of …
Optimizing Human Resource Decisions: Predicting Promotions Using Data Analytics, Mohammad Khalid A Mohammad Abdulrahim
Optimizing Human Resource Decisions: Predicting Promotions Using Data Analytics, Mohammad Khalid A Mohammad Abdulrahim
Theses
Proper and objective selection of high potential employees to promote them is a major dilemma in the Human Resources (HR) department, more so in sensitive and hierarchal environments in the public sector where subjectivity is likely to take place. This paper is based on this ubiquitous issue, and it seeks to develop, experiment, and examine a clear and equitable machine learning model that can forecast the possibility of an employee to get a promotion according to organized past HR records. The technique was solid preprocessing, alleviation of extreme class imbalances on the basis of the Synthetic Minority Over-sampling Technique (SMOTE), …
Deepfake Audio Detection, Rashed Alfalasi
Deepfake Audio Detection, Rashed Alfalasi
Theses
The rise of deepfake audio technology has introduced a serious threat to information credibility, personal security, and media integrity. This thesis investigates the application of machine learning techniques for detecting synthetic audio through the analysis of acoustic features, including Mel-Frequency Cepstral Coefficients (MFCCs), spectral centroid, chroma_stft, and zero-crossing rate. The dataset used in this study was sourced from Kaggle and contains labeled samples of real and fake audio clips. The research aimed to train and evaluate multiple machine learning models—Support Vector Machines (SVM), Random Forest, XGBoost, Logistic Regression, and Neural Networks—to determine the most effective approach for deepfake audio classification. …
Security Vulnerabilities In Cloud Storage: A Comparative Study Of Google Drive, Dropbox, And Onedrive, Sultan Majid Alshamsi
Security Vulnerabilities In Cloud Storage: A Comparative Study Of Google Drive, Dropbox, And Onedrive, Sultan Majid Alshamsi
Theses
In recent years, use of internet has increased manifold. People have started creating more data, and instead of saving it locally, people have started preferring storing it “online”. Companies are also following the same path to maintain accessibility and availability of their data. Thus, data has become a central part of our lives. People, companies, and institutions rely heavily on cloud storage solutions these days for managing their data. Some of the main cloud storage solution are Google Drive, Dropbox, and OneDrive. These are sophisticated solutions developed by tech giants, and general expectation of the public is that these solutions …
Work And Play In Tandem: A Brief Study Of Familiar Silhouettes In The Contemporary Workplace, Tanisa Bose Samaddar
Work And Play In Tandem: A Brief Study Of Familiar Silhouettes In The Contemporary Workplace, Tanisa Bose Samaddar
Theses
This thesis addresses the limitations posed by conventional office furniture, and its impact on human psychological and physiological well-being. Drawing upon literature that delves into the topics of neuroscience of play, environmental psychology, and emotional sustainability, the thesis seeks to solve these issues through design modifications. It aims to understand how brief, movement-focused breaks can help rejuvenate executive functioning, uplift mood, and encourage bursts of social interaction. A five-stage prototyping process, thumbnail sketches, clay models, 3D modeling, full-scale drawings, and iterative Fusion360 refinements, later Tandem was born. By requiring at least two users to operate its see-saw mode, Tandem counteracts …
Analyzing Airline Customer Experience Challenges And Their Impact On Dubai's Tourism Sector, Suhail Alfalasi
Analyzing Airline Customer Experience Challenges And Their Impact On Dubai's Tourism Sector, Suhail Alfalasi
Theses
The paper explores whether there is a connection between operational performance, customer sentiment, and digital administrative complexity among major regional Middle Eastern airlines, such as Flag Carriers (e.g., Emirates) and Low-Cost carriers (LCCs) (e.g., Air Arabia). With the use of a highly detailed dataset of customer review and operations data, the study proves that a large service paradox is present in which, despite the high Net Promoter Scores (NPS: 48.004) of the carriers, which are positively reinforced by delivering world-class soft products, the loyalty is constantly disrupted by low-frequency but high-severe operational delays (Delay_Minutes). Since it has been analyzed that …
Ai-Driven Cyber Threat Detection, Humaid Thani Almheiri
Ai-Driven Cyber Threat Detection, Humaid Thani Almheiri
Theses
Bycreating an AI-driven method using deep learning and statistical analysis tools, this study seeks to fill important security holes in conventional intrusion detection systems. Current signature-based systems miss new and complex cyberattacks, which have significant financial and operational consequences for companies. The suggested approach detects unusual network activity in real-time by combining statistical analysis with long short-term memory networks (LSTMs), convolutional neural networks (CNNs), and statistical analysis. This study will create and test hybrid models that can identify both known and zero-day threats while reducing false positives using publicly accessible datasets like UNSW-NB15, CIC-IDS2017, and NSL-KDD. Expected results are a …
A Comparative Analysis Of Machine Learning And Deep Learning Models For Human Activity Recognition Using Wearable Sensor Data, Fares Shaban
A Comparative Analysis Of Machine Learning And Deep Learning Models For Human Activity Recognition Using Wearable Sensor Data, Fares Shaban
Theses
Wearable sensors have become vital for health monitoring, evaluation of sport performance, and recognition of activities of daily life in Human Activity Recognition (HAR). With the combination of machine learning and inertial sensing, new possibilities for the collection of data pertaining to human motion in daily life have emerged. Nevertheless, problems remain to be resolved in the field of modeling in relation to tradeoffs in classification. The focus remains on imaging, signal variability, and sensor noise. This study aims to determine the usefulness of Inertial Measurement Unit (IMU) data for activity recognition and compares classical machine learning methods with a …
Modeling Economic Effects On Climate Change, Ahmed Abdulqader
Modeling Economic Effects On Climate Change, Ahmed Abdulqader
Theses
Climate change represents one of the most critical challenges facing the global economy today. While environmental impacts receive considerable attention, the economic implications are equally significant and require rigorous quantitative analysis. This thesis investigates the relationship between climate change and major economic indicators including GDP growth, inflation, trade balances, and employment across 50 countries from 1990 to 2023. The research employs a comprehensive multi-methodological approach combining panel data econometrics, time-series analysis, and machine learning techniques. Fixed-effects and random-effects panel regression models reveal statistically significant relationships between climate-related disaster frequency and economic performance. Specifically, disaster count demonstrates a positive coefficient of …
A Ux Approach To Improving Patient Experience In Healthcare, Lingxin Sun
A Ux Approach To Improving Patient Experience In Healthcare, Lingxin Sun
Theses
Doc Ease is a UX research and design project that addresses the emotional and functional difficulties patients experience before visiting a doctor. Through user interviews, competitive analysis, and design iteration, this project identified key user pain points such as unclear appointment processes, lack of trust, and pre-visit anxiety. The resulting mobile app offers clear booking tools, visual doctor information, medication reminders, and an emotional wellness module to help patients prepare with confidence. The project contributes to the field of healthcare UX by integrating functional usability with emotional care, proposing a design framework that centers patient experience in both logic and …
Assessing The Impact Of Codec-Induced Audio Degradation On Voice Biometric Systems, Suhil Ali Almuhaisni
Assessing The Impact Of Codec-Induced Audio Degradation On Voice Biometric Systems, Suhil Ali Almuhaisni
Theses
This study examines the robustness of voice biometrics when speech signals undergo audio codec transformations and sampling rate variations, conditions common in telecommunication networks. Speaker verification systems such as ECAPA-TDNN perform well on clean datasets, but their accuracy declines when low-bitrate codecs compress speech or when signals are resampled at reduced frequencies. In real-world deployments, systems adapt audio to bandwidth and storage limitations, often removing subtle acoustic details that support consistent speaker recognition. The research will analyse how codec settings and sampling rates, particularly those optimized for efficiency in bandwidth-limited systems, influence the stability of speaker embeddings. Instead of ranking …
Beyond Detection: A Batch-Based Ai Framework For Temporal And Event-Correlated Trend Analysis Of Misinformation On Social Media, Vishnu Tejas Vijayaraghavan
Beyond Detection: A Batch-Based Ai Framework For Temporal And Event-Correlated Trend Analysis Of Misinformation On Social Media, Vishnu Tejas Vijayaraghavan
Theses
The rapid spread of misleading information on social media influences public behaviour and complicates crisis communication. Although transformer models such as BERT accurately detect misinformation at the post level, most studies analyse posts in isolation and overlook howmisinformation fluctuates over time or responds to major events. This study addresses that gap by developing an end-to-end analytical workflow that integrates BERT-based classification with temporal aggregation, topic clustering, anomaly detection, and event alignment. The analysis uses 10,700 COVID-19–related tweets (6,420 training, 2,140 validation, and 2,140 testing). Because timestamps were unavailable, synthetic timestamps were assigned using an evenly spaced date range between 1 …
An Examination Of High-Entropy Alternatives Of Connectionist Temporal Classification Loss For Optical Music Recognition Using Convolutional Recurrent Neural Networks, Hritik Saynganthone
An Examination Of High-Entropy Alternatives Of Connectionist Temporal Classification Loss For Optical Music Recognition Using Convolutional Recurrent Neural Networks, Hritik Saynganthone
Theses
The Connectionist Temporal Classification (CTC) loss function is the most commonly used loss function in the field of Optical Music Recognition (OMR). However, OMR suffers from a massive class imbalance problem, exacerbated by the fact that CTC loss is subject to the spiky distribution problem, wherein the blank token introduced by CTC is vastly overpredicted and appears in timesteps where it would make more sense to predict a non-blank token, since CTC will collapse repeated tokens into a single token. This work posits that alternative loss functions to CTC that optimize for an increase in entropy of the prior probability …
Hyaluronic Acid Loaded With Aloe Vera-Derived Extracellular Vesicles: A New Bioactive Approach For Fibrotic Scarring, Maria Camila Ceballos Santa
Hyaluronic Acid Loaded With Aloe Vera-Derived Extracellular Vesicles: A New Bioactive Approach For Fibrotic Scarring, Maria Camila Ceballos Santa
Theses
Disruptions in wound healing can result in pathological outcomes ranging from chronic nonhealing wounds to excessive fibrotic scarring. Hypertrophic scars and keloids are hallmarks of this dysregulation, characterized by abnormal collagen deposition, persistent myofibroblast activation, and disorganized extracellular matrix (ECM) remodeling. Chronic inflammation and oxidative stress play central roles by increasing reactive oxygen species (ROS), which damage essential macromolecules and sustain pro-inflammatory signaling, while promoting the transdifferentiation of fibroblasts into myofibroblasts and the excessive production of ECM proteins, such as collagen and α-smooth muscle actin (α-SMA). This fibrotic cascade leads to tissue stiffness, contractility, and disfigurement, affecting the well-being of …
Mixed-Integer Linear Programming (Milp) Model For Transportation Cost Optimization, Yasmen Ghonim
Mixed-Integer Linear Programming (Milp) Model For Transportation Cost Optimization, Yasmen Ghonim
Theses
Motivated by a request from a real company, this study presents a mixed integer linear programming (MILP) model for labor transportation at real company located in Dubai (BSG). The study integrates routing, assignment, and environmental pricing into one model, with the focus on fixed shift worker transport and featuring several dorms and sites. It also tests the model with the real company data from the UAE service sector. The model assigns workers from dormitories to the client sites by busses in a manner that minimizes daily transport cost and monetized CO₂ emissions, subject to capacity, routing, and utilization constraints. The …
A Comprehensive Digital Marketing Strategy Guide For Independent Musicians, William Elree Hilburn
A Comprehensive Digital Marketing Strategy Guide For Independent Musicians, William Elree Hilburn
Theses
Creating and implementing a sound digital marketing strategy is a crucial element to consider as an independent musician. In this thesis report and the strategy guide that follows, a number of current digital marketing strategies are discussed at length. The strategies that are discussed in this report and within the strategy guide have been gleaned through semi-structured qualitative interviews with two separate up-and-coming music artists. The information shared by these case studies has been documented and synthesised into this report, as well as, into a comprehensive strategy guide that has been written to aid fledgling music artists in their digital …
A Comparison Of Fixed And Repetitive Models During Imitation Training In Children With Developmental Delays In A School Setting, Laci Fletcher
A Comparison Of Fixed And Repetitive Models During Imitation Training In Children With Developmental Delays In A School Setting, Laci Fletcher
Theses
Imitation training is commonly recommended in applied behavior analytic literature to address deficits in imitative skills. Few studies have directly compared imitative models to identify the most efficient and effective teaching arrangement to facilitate imitative skills (Deshai & Vollmer, 2019; Halbur et al., 2023). Previous results are inconclusive, and the authors recommended further research comparing the effect of fixed and repetitive models. Therefore, the present study was a replication of Halbur et al. (2023) and addressed limitations suggested by the authors. We examined whether components of imitative models affected the efficiency of the model type and reduced faulty stimulus control …
Exploring The Relationship Between Social Media And Anxiety In Deaf Community Students: A Mixed-Methods Approach., Gigi Zheng
Theses
The mental health of Deaf individuals, particularly in relation to social media engagement, is an understudied area amid growing global concerns about anxiety disorders. Deaf individuals face unique challenges, including communication barriers, social isolation, and stigma, all of which can heighten anxiety levels. Although social media offers valuable opportunities for connection and self-expression, it may also amplify stress and feelings of inadequacy when accessibility barriers persist. This mixed-methods study examined anxiety among Deaf college students and explored the cultural validity of two widely used anxiety measures—the State-Trait Anxiety Inventory (STAI) and the Beck Anxiety Inventory (BAI). Quantitative data were collected …
Ecotheology For Kids, Lana Glenn
Ecotheology For Kids, Lana Glenn
Theses
This project includes research into the eco-anxiety of children and how ecotheology may help ease the children’s minds. This project is meant as a sign of hope in the climate crisis; there are so many reasons to look forward to ecological improvements for the Earth. As adults, we should remind children of these reasons to be hopeful for the future. This 24-page book has illustrations with prayers to help calm the readers, while the cover is informational and inviting.