Computer Sciences Commons^™

Automated Segmentation Of The Ulnar Nerve In Mri Using Deep Learning Techniques, Akhil Nagulapalli

Theses

Cubital Tunnel Syndrome (CuTS), a condition caused by compression of the ulnar nerve, results in numbness, tingling, pain, and even muscle atrophy, affecting fine motor skills and diminishing patient quality of life. Accurate diagnosis of CuTS is challenging, as current diagnostic methods—including clinical exams, nerve conduction studies, and unaided MRI—often lack the precision to reliably identify the nerve and detect compression in its early stages. Deep learning-based segmentation offers a promising solution, enabling precise and automated identification of nerve structures in MRI images, which could significantly improve diagnostic accuracy and support timely intervention.

A novel deep learning model for segmenting …

Applications Of Neural Networks In Parkinson’S Disease Diagnosis, Saladin Minhaaj

Theses

Parkinson's disease (PD) is a complex and debilitating neurodegenerative disorder that affects millions of people worldwide. Early and accurate diagnosis is crucial for effective treatment and management of PD. This thesis explores the application of neural networks in PD diagnosis, leveraging their ability to learn patterns from large datasets and make accurate predictions.

Thesis provides an overview of PD, including its symptoms, diagnosis, and current challenges in diagnosis. We then delve into the fundamentals of neural networks, including supervised learning, mathematical interpretations, and parametric models. This research focuses on the development of neural network models that can accurately diagnose PD …

Holistic Correlation Measure For Enhanced Encapsulation Of Trait Heterogeneity And Discovery Of Co-Expression, Zachary Valleroy

Theses

Large-scale, high-dimensional data analyses can be computationally prohibitive due to combinatorial explosion of the search space for finding complex patterns; a viable alternative is network modeling for abstraction and quantifying intrinsic data associations. Prominent network analysis methods furnish frameworks for model synthesis and validation but rely on standard correlation measures impaired by semi-supervised biases, latent heterogeneity, and uneven discretization techniques. Here we investigate a holistic measure for encapsulating data heterogeneity for enhanced efficacy of revealing complex patterns through network analysis. Our unique correlation metric, K-medoids Utility for Duo Original Similarities (Kudos), exhaustively factors real-valued analyte data to compute …

Developing Policies For Digital Twin Data Quality And Security Controls, Ahmad Abdelbaset Hassan

Theses

This thesis is concerned with the data quality and security of the digital twin and how it is going to impact its adoption, trustworthiness, and potential for real-world applications. By addressing the potential vulnerabilities and ensuring the integrity of data, this research aims to contribute to the development of robust and trustworthy digital twin policies that to complement the existing international standards across different domains. Moreover, it underscores the important need to establish robust policies to ensure the successful and secure deployment of digital twins across industries. Previous research, while valuable, may not have fully addressed the critical interplay between …

A Secure And Effective Framework For Key Concept Mining From Educational Content Using Large Language Models, Ashika Sameem Abdul Rasheed

Theses

This thesis examines the use of Large Language Models (LLMs) in education, with a focus on improving performance and implementing strong security measures. The research has two main goals, namely, the development of an effective lecture summarization technique using LLMs and identifying and addressing security vulnerabilities in LLM applications according to OWASP (Open Web Application Security Project) guidelines. For the former goal, we have proposed an effective framework for fine-tuning LLMs using real lecture datasets and compared the performance of different LLMs. For the latter goal, we conducted a thorough review of the application dataflow of the proposed framework and …

Ai-Powered Pedagogy: Revolutionizing Students’ Learning Experiences Through Integration Of Ai Technologies, Amna Awad Alsaedi

Theses

This research examines the integration of Artificial Intelligence (AI) within the educational sector with the aim of enhancing student learning outcomes. AI offers tailored learning experiences, interactive educational content, prompt feedback, and access to diverse learning resources. Nonetheless, challenges including addiction, costliness, privacy infringement, bias, ethical dilemmas, market competition, and moral considerations require resolution. Research particularly delves into the utilization of chatbots, and algorithms designed to simulate human interactions and generate text resembling human speech. Educational applications powered by AI have the potential to heighten student engagement, comprehension, and academic performance by substituting traditional assignments with concise, information-rich lessons. Furthermore, …

Effect Of Virtual Reality Technology On Computer Science/Engineering Based Laboratories Education – A Case Study, Mariam A. Al Nuaimi

Theses

Virtual reality (VR) is becoming increasingly popular and essential in education as institutions strive to incorporate technology in education. In Engineering and Computer Science, students face difficulties in comprehending many abstract complex concepts that are typically studied in Labs. This situation worsens with hardware failure and the lack of pedagogical tools. The main goal of this paper is to investigate the impact of VR environments on learning advanced and complex STEM concepts. We also explore the impact of different human-computer interaction (HCI) techniques including gamification on the learning experience of STEM students. To measure such impact, we developed a VR …

Effect Of Virtual Reality Technology On Computer Science/Engineering Based Laboratories Education – A Case Study, Saeed Salem Al Shebli

Theses

The rapid growth in mobile applications raises critical concerns about the security of apps and users' privacy, especially in permission control. Mobile apps access sensitive information of users, and the current cybersecurity landscape faces a huge challenge in ensuring the least required permissions are granted. This research focuses on designing an advanced permission recommendation system that couples the strengths of Natural Language Processing (NLP) and Machine Learning (ML) in solving most of the existing gaps in permission management, thus guiding which permissions are mostly needed by Android applications.

The research thus follows a multi-classification approach, integrating state-of-the-art ML techniques with …

An Edge Platform Streamlining Connectivity Between Modern Edge Devices And Cloud, Anderson Carvalho

Theses

The numerous uses of cloud, fog, and edge computing in a variety of industries are thoroughly examined in this thesis, with a special emphasis on smart factories, smart cities, and smart agriculture. It starts with an introduction to cloud computing, going over its history, importance in contemporary digital infrastructures, and related security concerns. It emphasizes the value of cloud computing for processing and storing data while addressing issues like guaranteeing low latency applications and possible improvements from container technologies. The conversation then shifts to fog computing, going over its history, designs, and uses. It focuses on how fog computing might …

Securing The Inbox: Advancing Phishing Email Detection With Fine-Tuned Bert, Fatima Rashed Al Saedi

Theses

In recent years, phishing attacks have persisted as a widespread threat in the contemporary digital environment, presenting substantial risks to individuals and organizations. Cybercriminals are devising increasingly sophisticated strategies to deceive users through malicious emails. In response to this challenge, this research focuses on developing a new tool for detecting phishing emails utilizing the BERT algorithm. The tool aims to enhance email security by accurately identifying deceptive emails and protecting users from potential cyber threats. The primary objective of this study is to investigate how leveraging the BERT algorithm can improve the detection of phishing emails compared to traditional methods. …

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 …

Visualizing Privately Protected Data: Exploring The Privacy-Utility Trade-Offs, Sarah Hayi Alkaabi

Theses

In a data-driven era, achieving a balance between privacy and utility is crucial. Organizations often utilize data for research, analysis, and enhancement of services, which emphasizes the significance of effective privacy-preserving techniques to protect individuals' privacy and comply with regulations. This equilibrium is vital in data visualization to derive insightful decisions from data representations. The goal is to evaluate the trade-off between privacy preservation and data utility, understanding how differentially private parameters impact effective visualizations. Valuable insights will guide strategies for achieving optimal privacy-preserving visualization techniques. The study aims to investigate the effects on privacy and data utility in different …

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 …

Vascular Brain Digital Twins For Medical Training And Education In Metaverse, Shamma Khaled Alghafri

Theses

This study addresses the need for innovative educational tools in the field of anatomy, specifically focusing on brain anatomy. The objective is to develop a virtual reality application and a 3D visualization that offer immersive and interactive learning experiences for students. The VR application, developed using Unity and designed for the Oculus Quest 2 headset, creates an immersive virtual laboratory environment. This environment includes interactive elements such as a table with buttons for displaying brain models and a whiteboard for user interaction. Users can manipulate and explore different brain structures, enhancing their understanding of complex anatomical features. Additionally, we integrated …

White Cell Support Application For Expo Ops Tactical Wargame System, Zackery Joseph Milder

Theses

The purpose of this project was to create a support application for a tabletop wargame currently used for training and scenario simulation by the United States Marine Corps. The EXPO OPS Companion is meant to enhance the capabilities of the White Cell/table director, the unbiased third party responsible for running adjudication for the EXPO OPS Tactical Wargames System. EXPO OPS TWS is “…a table top wargame covering contemporary and future conflict at the platoon, company and battalion level. It is a wargame toolkit that enables wargaming scenarios in the 2020 to 2030 timeframe. The design centers on plans and decisions …

The Impact Of Ai On Ux: Challenges And Opportunities, Susan Stephanie Wells

Theses

Integrating artificial intelligence (AI) in user experience (UX) design is reshaping the field of UX, offering new opportunities and challenges for designers. This thesis project explores the multifaceted relationship between AI and UX design, focusing on the challenges, opportunities, and skills demanded of UX designers in the age of AI. Through a review of academic research and real-world experiences, this project studies the impact of AI on web design processes, UX testing, and data analysis. Key findings highlight the transformative potential of AI in enhancing user experiences, from suggesting website structures to facilitating UX testing and data analysis.

Comparative analysis …

An Intelligent Academic Advising System For Course Recommendation Using Large Language Models, Malika Maya Iratni

Theses

Academic advising is an important resource for students, especially in higher education, in order to guide them to make the best possible decisions to improve their overall academic performance and overall academic journey. With the increasing number of students joining these institutions each year, traditional advising becomes a time-consuming and inefficient process that can leave students discouraged, and advisors overwhelmed. Therefore, there is a need to develop intelligent advising systems that make use of the recent advancements in technology, to support the advising process, and increase overall student satisfaction. In this work, an academic advising model that uses Recommender Systems …

Towards Erasing The Distinction Between The Computational And Syntactic Accounts Of Scientific Theories, Timothy Luft

Theses

One of the main goals of philosophy of science is to give a proper account of scientific theories and their structure. One way that accounts of the structure of scientific theories can be distinguished is by the mathematical or logical structures that they involve. For instance, syntactic accounts of scientific theories hold that theories are axioms in a logical framework, whereas semantic accounts are more liberal in the range of mathematical and logical structures they take as pertinent to the structure of scientific theories. Paul Thagard (1988) offers a computational account of scientific theories, which holds that theories are complex …

Unearthing The Past: A Comprehensive Study Of Natural And Anthropogenic Changes At An Archaeological Site Through Hydrogeologic Connectivity Utilizing Gis, Mehlich Ii Phosphorus Extractant, And Ph, Dana L. F. Herren

Theses

This thesis aims to thoroughly analyze the Mehlich II Phosphorus Extractant and pH levels at the Bains Gap Village Site in Anniston, AL., while examining the impact of various environmental factors and human activities on them. Phosphorus is often used in archaeology as an indicator of human activity. Soil core samples were collected to analyze anomalies in phosphorus levels.

To establish any relationships, phosphorus and pH levels from soil cores were correlated with findings from past excavation units and features. The potential effects of hydrogeologic connectivity on soil phosphorus and pH levels were investigated. Geospatial technologies were used to manage …

Unveiling The Origins Of Source Code Through Authorship Attribution: A Comparative Study Of Ai And Human Coding Patterns, Shamma Humaid Alalawi

Theses

In recent years, Artificial Intelligence (AI) techniques have been used for source code authorship attribution, which is the process of identifying the original author of a given piece of code. With the advancement of AI technologies like ChatGPT, which can generate code, there is a need to accurately identify whether a piece of code is written by a human or generated by a machine. This is crucial for intellectual property protection, cybersecurity, and software forensics. The main objective of this thesis is to review existing research on source code authorship attribution and conduct several experiments to determine the best AI …

Integrating Artificial Intelligence For Automated Storytelling In Turn-Based Strategy Games, Timothy Ripper

Theses

This project is inspired by turn-based strategy games, Final Fantasy Tactics, X-Com 2, and modern turn-based strategy games. This project is structured around the use of artificial intelligence for storytelling within strategy games. The focus of this project utilizes artificial intelligence in creating a quest generation system for storytelling. The resulting quest system creates new quests dynamically after communicating with an artificial intelligence allowing players to potentially experience an ever-expanding story from quests

Enhancing Cybersecurity Awareness In The United Arab Emirates: An Assessment Of Current Practices And The Development Of An Ai-Enhanced Mobile Application, Meera Humaid Alalawi

Theses

In today's interconnected world, individuals, private corporations, public institutions, and governments face increasingly sophisticated cyber threats and attacks, highlighting the critical need for individuals and organizations to understand cybersecurity comprehensively. Cyberattacks have affected many countries and infrastructures in different sectors worldwide, including the United Arab Emirates (UAE), which has become a main target for cybercrime due to its booming economy and tourism. The UAE considers cybersecurity an increasingly critical issue in our digital world, and increasing cybersecurity awareness among residents is essential to protect themselves and their organizations from cyberattacks. The primary objectives of this study are to identify key …

Intelligent Tutoring System Ontology, Wael Mohamed Hassan

Theses

The integration of pedagogical rules into Intelligent Tutoring Systems (ITS) using semantic web technologies, particularly the Web Ontology Language (OWL), holds great promise for enhancing the capabilities of these systems. However, a significant challenge arises from the labor-intensive process of manually constructing ontologies, which can consume valuable time and resources. While ontologies offer numerous advantages, including robust knowledge inference and scalability, the limitations of manual ontology creation are evident in terms of time and flexibility. Therefore, the primary objective of this research is to develop an efficient and automated solution that harnesses the benefits of ontologies while reducing the time …

Marketing Video Games To Aging Demographics: A Generational Profile Analysis, Brinna Louise Ball

Theses

Marketing video games to aging demographics like Baby Boomers, Generation X, and Millennials requires a unique approach by video game studios and consumer products divisions alike. The strategies employed for younger generations such as Generation Z and Generation Alpha differ from conventional methods, requiring a fresh outlook and a need for more innovative and inventive approaches. To comprehend the current aging audience more effectively, it's essential to examine four crucial factors: accessibility, exposure, media habits, and motivations to play video games. Examining these factors by generation, we can better grasp how to effectively market video games to these demographics. It's …

Future-Proofing The Past: Artificial Intelligence In The Restoration Of Andalusian Architectural Heritage: A Case Study Of The Alhambra Palace, Granada, Spain, Kholoud Bader Hasan Ghaith

Theses

This thesis explains the contribution of artificial intelligence in heritage restoration as an icon of Andalusian architecture by using the Alhambra as an example. The task of sustaining heritage is increasing dramatically due to the accumulation of heritage assets and the need for modern and innovative operations to cope with preservation tasks. Therefore, this thesis reviews the role of artificial intelligence in improving the restoration operation to improve accuracy and efficiency. I applied the case study as a scientific methodology to explain this work to overcome scientific and subjective obstacles, such as scarce data and software integration while explaining the …

Fast And Reliable Authentication Method For Indoor Constrained Drones, Fatima Ali Al Nuaimi

Theses

Over the last twenty years, the commercial sector of Unmanned Aerial Vehicles has been growing exponentially, owing to their rapid deployment, high mobility, and the number of applications in the industry field such as military, transportation, critical infrastructures, as well as in the academic field for research purposes. One of the main communication systems adopted by the UAVs relies on transmitting wireless signals.

In particular, UAVs are adopted for indoor use-case scenarios, such as warehouse inventory applications and indoor building inspections. They need to transmit control messages and sensitive data by leveraging an efficient, short-range, and secure communication channel to …

Assessing Open Source Tools For Enhanced Forensic Analysis Of Unmanned Aerial Vehicles (Uavs), Nura Shifa Hamed

Theses

The widespread applications of Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, has given rise to significant national security threats due to their illicit activities. Consequently, the domain of UAV forensics is rapidly evolving, presenting a substantial knowledge deficit among forensic experts. Open source tools provide accessible and affordable resources, making it easier for investigators to bridge this gap by gaining expertise in the use of these tools. This helps ensure that forensic professionals can keep up with the ever-changing UAV technology landscape. This thesis undertakes the mission of navigate the complex field of drone forensics and conducting a …

Discourses Across Periods Of Time, Amanda Raquel Moreno

Theses

This literature review explores the revolutionary effect of generative artificial intelligence (AI) and virtual reality (VR) on digital art history, specifically concentrating on their capacity to enable dialogical exchanges with historical figures and deepen the understanding of artworks. This study considers the current state of research, detecting key methodologies, areas of improvement, and possible challenges and ethical concerns. The example historical figure used in this analysis is the iconic Mexican artist Frida Kahlo. Kahlo’s refusal to correspond to a specific artistic style makes her an ideal subject for generative AI and VR-based investigation, offering fresh insights into her work. The …

An Empirical Study On The Use Of Secure Predictive Analytics For Improving Trade Forecasting In The Uae, Asma Salem Alneyadi

Theses

Trade contributes to the United Arab Emirates' economic growth. This thesis focuses on trade dynamics in the UAE using Long Short-Term Memory (LSTM) neural networks. The study focuses on both import and export activities, providing understandings into the complex patterns and impacts of international trade on the UAE's economic growth. The research begins by constructing an LSTM model to forecast the UAE's Gross Domestic Product (GDP) through the utilization of historical trade data. We use time series data for imports and exports as key input features. This innovative approach highlights the relevance of trade statistics as a leading indicator of …

Dress-Code Violation Detection In Arabic Regions Using Object Detection Machine Learning Model, Maha Sadat Aghaei

Theses

The dress code violation detection system is crucial for assessing clothing appropriateness in public areas. This study aims to improve this system using advanced computer vision and machine learning techniques to more effectively categorize people's attire in images and videos. To enhance adaptability and create a user-friendly graphical interface for system management and deployment, we have generated a unique dataset from various contexts mix of Western and Arabic clothing. This allows users to interact with graphical components, including the ability to upload images or use live video for clothing detection. Moreover, we have taken privacy concerns into account and implemented …