Digital Commons Network^™

Rental Property Demand And Supply Analysis Using Machine Learning, Ahmed Amiri

Theses

The real estate market in Dubai is famous for its activity and stimulating potential due to the geographical position of the emirate, well-developed transport and legal framework. Timely determination and prediction of rental price is crucial for investors, property owners and managers, tenants and authorities in their decision making to maximize returns and ensure market stability. Traditional approaches are insufficient for the analysis of the temporal and spatial relations between property characteristics and market processes, which require the use of sophisticated machine learning algorithms. This paper aims to predict the rental prices of properties in Dubai using machine learning models …

Social Media Intelligence: Responding To Crime And Violence In The Digital World, Chloe Lynn Sitton

Theses

The integration of social media into everyday life has transformed how crime is committed, communicated, and investigated. This capstone project examines the emerging field of social media intelligence and its growing influence on modern policing, surveillance, and the community. Drawing from sociological theory, law enforcement practice, legal analysis, and community-based research, this project offers a far-reaching interdisciplinary view of how social media is shaping crime and justice in the United States.

Improving Obsolescence Management By Enhancing Supplier-Customer Collaboration, Mora Issa

Theses

There are currently many legacy facilities operating in the Middle East & Africa region that have plans in place to extend the plant life. Oil prices have been steadily going up, leading to increases in production, and driving economic growth. In order to extend the life of these older facilities, the sites are budgeting to replace critical parts accordingly. Obsolescence is an inevitable part of every product lifecycle and, with the new wave of technology and AI in the market, facilities face the challenge of increasing profitability in the fast-paced economy. The number of more efficient upgrades available presents an …

Analysis Of Team Size Effects On Technical Debt And Code Quality For Open Source Projects, Tyler Borrelli

Theses

Little research has been done to analyze the relationships between the amount of Technical Debt in an open source software project and the number of developers. This study seeks to identify the effects that team size and number of contributors have on Technical Debt and overall software quality. The results of the study observed after accounting for effects from code size that there was a negative correlation for issues with software quality, for example code smells or complexity, and the number of authors on a per file basis. This suggests that increasing the developer count most likely will not negatively …

Data Privacy Protection For Zero-Permission Sensors In Iot Systems, Xinyi Liu

Theses

The Internet of Things (IoT) has revolutionized various domains through real-time decision-making and automation, with sensors serving as foundational components. Zero-permission sensors, such as accelerometers and gyroscopes, are widely used in most IoT systems, enabling unrestricted data access without permission. Despite being traditionally perceived as low-sensitivity, recent studies have shown that these sensors can be exploited to infer sensitive personal information, raising serious privacy concerns. Local Differential Privacy (LDP) is a rigorous technique for numerical data privacy protection even when the data collector, such as an IoT service provider, is untrusted. LDP ensures privacy by adding noise to sensor readings …

Predicting Students At Risk Of Dropping Out In The College Of Medicine At Mohammed Bin Rashid University Of Medicine And Health Sciences. A Machine Learning Approach To Understand Attrition Factors Over The Past Seven Years, Moza Sulaiman Al-Zaabi

Theses

This master’s thesis investigates student attrition within the College of Medicine at Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU) by applying the CRISP-DM methodology to analyse a dataset of 19 variables and around 2,000 records from Student Admission and Academic Performance sources. Although the dataset was relatively small, several machine learning models were developed to predict students at risk of dropping out, including Logistic Regression, Decision Trees, Support Vector Machines (SVM), and Artificial Neural Networks (ANN). Of these models, the ANN model, particularly when combined with Principal Component Analysis (PCA), achieved the highest performance with an accuracy …

Donut Day, Amelia Krouse

Theses

Donut Day is a 2D animated short film that was produced by Amelia Krouse at the Rochester Institute of Technology from 2023-2024. It was her third short film produced, and was just over three minutes long. The short is a comedic narrative piece that depicts the struggles of an office worker chasing after a dropped ring.

Cognitive And Emotional Theory Of Mind In Eating Disorders: The Mediating Role Of Alexithymia, Morgan R. Johnson

Theses

A number of studies have documented deficits in theory of mind (ToM), or the ability to infer the mental states of others, among individuals with eating disorders (EDs). Much of this research has focused on emotional ToM, as opposed to cognitive ToM, where mental inferences do not contain affective content. Alexithymia, a difficulty in the ability to correctly identify and describe one’s emotions, has also been reported among individuals with EDs. Alexithymia was hypothesized to mediate the relationship between ED symptoms and emotional ToM, as it has been shown in past research to significantly mediate emotion processing deficits in those …

Ai-Driven Anomaly Detection In Cybersecurity, Mohamed Almansoori

Theses

India has witnessed a huge level of digitization in the last two decades which has greatly impacted its economy and society. But the increasing use of technology has also intensified the number and level of threats to cyberspace in the country. Signature-based detection systems that have dominated the cybersecurity field for years have not been up to the challenge of modern attackers who use more complex and diverse attack methods. These challenges are well understood and this research focuses on improving the cybersecurity anomaly detection in India during the period between 2003 and 2022 using advanced AI and machine learning. …

Chest Disease Classification Using Transfer Learning, Adarsh Neema

Theses

In the domain of medical diagnostics, the precise classification of chest diseases has become very important, particularly during the occurrence of the COVID-19 pandemic. This project proposes an innovative approach to automate the classification process through the usage of deep learning technique, and more specifically making use of convolutional neural networks (CNNs) and transfer learning, with a prime focus on the RESNET50 architecture. The primary objective is to develop a model which is intelligent enough to detect various chest conditions, including COVID- 19, viral pneumonia, bacterial pneumonia, and normal cases. Utilizing the rigorously pre-trained knowledge encoded within RESNET50, trained on …

Evaluation Of A Token Reinforcement System For Assignment Completion In Students With Educational Disabilities, Brandon O'Dell

Theses

Token reinforcement systems are an effective tool in applied behavior analysis. Studies as early as the 1960s and 70s have demonstrated the effectiveness of token economy from addressing the behaviors of psychiatric patients (e.g., Allyon & Azrin, 1965) to supporting the academic achievement of students in school settings (e.g., McLaughlin & Malaby, 1972) Most recently, Espinoza and Hackenberg (2024) discussed the history and effectiveness of token reinforcement, while providing practical recommendations for its application. The current study aimed to implement a token reinforcement system to increase assignment completion and accuracy in three eighth-grade students with various medical and educational diagnoses …

Comparative Analysis Of Artificial Intelligence And Statistical Models For Li-Ion Battery Cells State Estimation In Electric Vehicles, Rasha H.A. Tabasha

Theses

This graduate paper presents a comparative study of statistical modeling and Artificial Intelligence (AI) approaches for estimating essential parameters of lithium-ion (Li-ion) batteries in electric vehicles (EVs). The key parameters estimated in this study are voltage, current, and temperature of Li-ion battery cells in EVs. A precise state estimation is required to ensure safety operation, to optimize the Battery Management System (BMS), and to enhance the battery life. Variations in EVs batteries parameters may occur due to different reasons such as sensor faults or attacks. As a result, obtaining an accurate estimation is essential to maintain EV battery efficiency. Using …

Evaluation Of An Instructional Sequence To Promote The Emergence Of Convergent Intraverbals In Children With Autism, Jesika Woodard

Theses

Skinner (1957) defined intraverbal as a type of verbal behavior in which the

response form has no point-to-point correspondence with its verbal stimulus and is

followed by generalized conditioned reinforcement. Verbal behavior can be influenced

by multiple controlling variables, with convergent and divergent control being two

distinct types of this influence. In convergent intraverbals, multiple components of

antecedent verbal stimuli control a specific verbal response of the speaker. An example of

an intraverbal response under convergent control may be "banana" when asked, "What is

a fruit that is yellow?" De Souza et al. (2019) evaluated the effects of teaching …

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 …

Integrative Hyperspectral Approaches For Advanced Soil Property Analysis And Environmental Monitoring, Nayma Binte Nur

Theses

Hyperspectral imaging has emerged as a powerful tool for enhancing the analysis of diverse soil properties and environmental monitoring. This study refines the precision of soil biogeophysical analyses by improving the estimation of soil moisture content (SMC), soil organic matter (SOM), total carbon (C), and nitrogen (N) through hyperspectral remote sensing techniques. The research examines the capabilities of two prominent moisture retrieval models: the multilayer radiative transfer model (MARMIT) and the modified soil water parametric (SWAP)-Hapke model. These models are evaluated using hyperspectral imagery derived from unmanned aerial systems (UAS) and goniometric data collected across various environmental settings. The findings …

Near Real-Time Center Of Gravity Estimation Of An Unmanned Aerial Vehicle, Carola Vasquez

Theses

As UAV technology advances and finds broader applications across industries, real-time estimation of the center of gravity (CG) becomes crucial for ensuring safe and efficient flight. Accurate CG estimation is vital not only for UAVs but also for manned aircraft, as it significantly influences stability and control by indicating the point where the entire weight is evenly distributed. Variations in CG, resulting from changes in altitude, attitude, speed, fuel consumption, and payload, directly impact stability and may lead to compromised performance and increased risk of accidents if not monitored. Existing methods focus on regression analysis, multi-accelerometer measurements, and pitching moment …

Understanding The Relationship Between Humble Leadership, Reflecting Dialogue, Psychological Safety And Job Satisfaction: A Study Of Japanese Correctional Officers, Yayoi Kimura

Theses

This study investigates the relationships between humble leadership, reflecting dialogue, psychological safety, and job satisfaction among correctional officers in Japanese correctional institutions. Correctional officers face high levels of stress due to their demanding roles in rehabilitating and managing inmates, yet the impact of organizational factors on their job satisfaction remains underexplored. As Japan undergoes significant changes in its penal system, understanding the factors that contribute to a supportive work environment is crucial. First, this study examines the relationship between psychological safety and job satisfaction among correctional officers. Second, it explores whether facilities that practice reflecting dialogue and humble leadership experience …

Using Machine Learning For Road Accident Severity Prediction And Optimal Rescue Pathways, Mohammad Yousuf Sulaiman Alhashmi

Theses

Road traffic accidents remain a critical challenge for urban planners, transportation authorities, and public safety stakeholders worldwide. Despite advancements in road infrastructure and traffic management, the frequency and severity of accidents continue to strain emergency response systems and compromise public safety. Accident hotspots, are particularly concerning, as they often exhibit recurring patterns of accidents due to factors such as poor road design, high traffic density, and adverse weather conditions. This thesis addresses the challenge of predicting accident severity and identifying accident-prone areas through a data-driven approach. Using a large dataset of over 7.7 million accident records containing geographical, environmental, and …

Temporal Analysis And Prediction Of Air Quality Based On Environmental Data, Mizbah Syed

Theses

Air pollution is one of the most pressing environmental challenges of the modern era, significantly impacting public health, ecosystems, and economic stability. Pollutants such as PM2.5, PM10, and NO₂—largely driven by urbanization, industrialization, and vehicular emissions—have exacerbated global health issues, including respiratory illnesses, cardiovascular diseases, and premature mortality. According to the World Health Organization, air pollution contributes to over 7 million deaths annually, with economic losses amounting to billions of dollars. Beyond its health and financial toll, air pollution worsens climate change, underscoring the urgent need for accurate air quality index (AQI) prediction to enable timely interventions and evidence-based policymaking. …

Beauty In The Mundane, Madeline Caniglia

Theses

This project focuses on challenging what compositions are considered valuable as art. The primary focus is on the relationship between light and shadow and how it contributes to the revelation of finding beauty in the mundane. This project involves studying old masters like Caravaggio and Edward Hopper while employing their techniques and methods in my artworks. Through a series of oil paintings, I depicted everyday objects and scenes to demonstrate how classical techniques, paired with contemporary subjects, help bridge historical and artistic practices with modern art.

Breaking The Grid: Metamorphosis And Materiality In Meret Oppenheim’S An Evening In The Year 1910, Jacklyn Meyer

Theses

This paper analyzes Meret Oppenheim’s painting An Evening in the Year 1910 from 1972 and its exploration of the theme of metamorphosis and materiality. Looking at certain biographical information about the artist’s crisis period and time spent with the Surrealist group is crucial in understanding what can be discerned from viewing this work. Other works with the theme of metamorphosis within her oeuvre are studied as they provide further context for Oppenheim’s artistic philosophy and her penchant for revisiting themes repeatedly. Other works with the theme of metamorphosis are studied as they provide further context for Oppenheim’s artistic philosophy and …

Beauty Beyond Barbed Wire: Chiura Obata’S Perspective Of The Horizon, Bri Carlson

Theses

Depictions of the environment are an integral part of American art history because they convey cultural relationships of all who inhabited the land. The environment is often a stagnant force that harbors lifetimes of human history. One of these histories is the incarceration of about 120,000 Japanese immigrants and American citizens in 1942 after the bombing of Pearl Harbor. They were forced to evacuate their homes, lives, and families to live in detention centers and prison camps where living conditions were subpar. Many turned to art making to cope, and some artists used their work to silently protest and visually …

Harnessing Federated Learning For Stock Analysis And Portfolio Optimisation, Nishanth Sagar Panthangi

Theses

Financial technology is rapidly transforming, with machine learning becoming crucial in stock analysis and portfolio optimization. Traditional stock analysis faces data privacy challenges when pooling data. Federated Learning addresses this by training models collaboratively without sharing raw data. This thesis explores Federated Learning in stock analysis, focusing on optimizing portfolio strategies using client-specific data.The proposed Federated Learning framework allows entities to develop independent models while maintaining data privacy. By combining diverse trading strategies, a global model is built, enhancing adaptability and predictive accuracy. The global model achieved a 25.08% CAGR and a Sharpe ratio of 4.46, outperforming individual models, which …

Project-Based Learning In Art History: Course Curriculum, Katelyn Baltes

Theses

The course entitled “Project-Based Learning in Art History” is a rigorous curriculum that introduces students to art history but creates a better understanding of how materials and techniques were used throughout time. Students in 11-12th grade will be able to apply their knowledge and learning through projects integrated within each unit to develop a stronger understanding of the content. Students will be able to apply the design elements and principles of design within their artwork and recognize the different characteristics of various periods and cultures. There will be the use of two-dimensional and three-dimensional art within each unit, and students …

Using Machine Learning To Predict Energy Consumption In Commercial Buildings In The Uae, Saif Nasser Aljasmi

Theses

The ever-growing demand for energy necessitates a shift towards efficient management practices. Buildings, responsible for a significant portion of global energy consumption, present a prime opportunity for optimization. Building Energy Management Systems (BEMS) have emerged as a crucial tool in this endeavor, offering a comprehensive platform for monitoring and integrating various building systems. However, a key functionality within BEMS, energy consumption prediction, has faced limitations in accuracy. This stagnation hinders the full potential of BEMS for achieving optimal energy management strategies. Traditional methods for energy prediction often rely on historical data and lack the sophistication to capture the complex and …

Recruitment Sources Of Grass Carp (Ctenopharyngodon Idella) In The Great Lakes, Nicholas Steven Etter

Theses

Grass Carp (Ctenopharyngodon idella) is a species of concern in areas they have invaded, such the Laurentian Great Lakes, due to their potential to substantially reduce aquatic macrophyte coverage. Efforts to control Grass Carp in the Great Lakes have primarily been focused on two tributaries to the western basin of Lake Erie (i.e., Sandusky and Maumee rivers, Ohio) where reproduction has been documented, although other Great Lakes tributaries are known to have thermal and hydrological regimes suitable for Grass Carp spawning. Knowledge of sources contributing to the expanding population of invasive Grass Carp in the Great Lakes is key to …

Second- And Third-Party Punishment In Common-Pool Resource Management, Jacquelyn Spence

Theses

Common-pool resources play a significant role in many economies, especially in developing countries where they are a critical source of food, income, and employment for communities. Long term management of common-pool resources can be challenging because the continued existence of the resource depends upon balancing the rate of resource depletion with the rate of repletion. Effective management of these resources is vital for protecting the environment and preserving the resources for future generations as overuse and degradation can have serious impacts on ecosystems and biodiversity. Elinor Ostrom’s design principles for common-pool resource (CPR) management provide valuable insight into human interaction …

Making Social Interactions Accessible For The Blind And Low-Vision People By Detecting Emotions Through Vocal Tone, Facial Expressions, And Body Language, Gautham Krishna

Theses

Despite the thriving research in the field of accessibility, there are several niche area where there is a need for specific solutions. One such area is social interaction. Blind and Low-Vision people (BLV) are limited in identifying emotions through verbal communication alone, which is often biased and unreliable in certain environments. Prior research illustrates the importance of body language in expressions and articulates the mechanism behind human emotions. Drawing inspiratoin from such research and various studies that were focused on emotion recognition systems, our research focused on identifying a portable accessible solution for BLV that classified emotion based on multi-modal …

Examining The Relationship Between Internalizing, Externalizing, And Psychotic Psychopathology At Five Levels Of Criminal Risk, Cooper Mitchell Sparks

Theses

Though it is well established that mental illness is not a primary risk factor for criminal justice involvement, the relationship between mental illness and criminal risk with justice-involved persons with mental illness is not well understood (Bonta, et al., 1998; Morgan, et al., 2010; Skeem, et al., 2014). Specifically, psychopathology has not been understood at different levels of criminal risk. Using the Five-Level Risk and Needs System for criminal risk (Hanson, et al., 2017), the current study aimed to identify mean differences between different domains of psychopathology (i.e., internalizing, externalizing, and psychotic psychopathology) across five levels of criminal risk. Data …

A Focus On The Social Validity Of Treating Stereotypy Using Response Interruption And Redirection, Maggie Grace Ratcliff

Theses

Stereotypy refers to a class of operant repetitive motor and vocal responses with no readily apparent goal or purpose (Rapp & Vollmer, 2005; Singer, 2009; Wunderlich et al., 2023). Although most stereotypy is clinically insignificant and does not warrant treatment (i.e., nail biting, hair twirling), some stereotypy persists at a frequency or severity which interferes with skill acquisition, social interactions, and daily living skills. Stereotypy which persists at this level is considered clinically significant and is often the target of treatment (Wunderlich et al., 2023). A variety of evidence-based treatments for the reduction of stereotypy exist, though some neurodiversity advocates …