Digital Commons Network^™

Segment-Level Machine Learning For Detecting Partial Deepfake Audio: An Rnn–Svm Hybrid Approach For Real-World Adversarial Environments, Ahmad Alhelli

Theses

This study investigates the detection of real, fully fake, and partially fake (PF) audio using classical machine-learning models as well as a segment-level analysis model. Unlike most existing research, which focuses solely on binary real-vs-fake classification, this work introduces a three-class detection framework and constructs realistic PF samples by inserting short synthetic speech segments into otherwise genuine audio recordings. Its method combines MFCC and spectral feature engineering,Wav2Vec2 embeddings, controlled PF synthesis and various models such as SVM, Random Forest, XGBoost and an attention based RNN. Segment level windowing allows fine-grained study of transition of time and breaks of manipulation. The …

Biodegradation Of Common Post-Consumer Plastic, Laura Krebs

Theses

Plastic waste is widespread throughout the Laurentian Great Lakes watershed. During environmental exposure, plastic undergoes abiotic and biotic degradation. The presence of novel plastic substrates coupled with rapid microbial turnover may lead to selection for or evolution of metabolic pathways and enzymes with enhanced biodegradation capabilities. This study investigated the biodegradation potential of bacteria isolated from debris accumulation hotspots - stormwater retention ponds, storm drains, and tributaries - in the Lake Ontario watershed within Rochester, New York. Bacterial isolates were exposed to commonly littered plastics for 240 d: cellulose acetate from smoked cigarette filters, high-density polyethylene from takeout shopping bags, …

Enhancing Airport Operations With Ai For A Seamless Passenger Experience, Rashed Alsubousi

Theses

The paper is research exploring the importance of Artificial Intelligence (AI) and Data Analytics to optimize airport operations and the passenger experience in the environment of the expanding air traffic in the world and the smart city movement. With increasing tasks that airports currently experience, congestion, flight delays, mishandling of baggage, and limited capacity, nowadays AI-based technologies integration is crucial to the operational efficiency, sustainability, and customer satisfaction. This study discusses the use of predictive analytics, machine learning, and clustering models to enhance passenger flows, resource allocation, and performance in general at airports. The research is based on the working …

Supervised Learning For Predicting Mental Health And Burnout In Healthcare Workers, Afra Alfalasi

Theses

This study aims to predict and analyze burnout among healthcare workers using supervised machine learning techniques and Exploratory Data Analysis (EDA). Leveraging the Healthcare Workforce Mental Health Dataset, the research identifies key demographic, occupational, and psychological factors most strongly associated with burnout. The methodology involves data preprocessing, feature selection, and model training using algorithms such as logistic regression, decision trees, random forests, and gradient boosting. Model performance will be evaluated through standard metrics, including accuracy, precision, recall, and ROC-AUC. The expected outcome is a predictive framework that highlights high-impact burnout predictors and generates actionable insights to support early intervention and …

Accelerating The Degradation Of Biodegradable Mulch Films In Soil And Compost Environments, Harshal Jayesh Kansara

Theses

The incomplete degradation of biodegradable mulch films (BMFs) in agricultural soils poses environmental challenges, with persistent plastic residues impacting soil health. This dissertation investigates the use of bioaugmentation with P. guariconensis to enhance BMF degradation under laboratory, raised bed, and field conditions. The research focuses on optimizing microbial delivery methods, evaluating the efficacy of drip and spray bioaugmentation techniques, and assessing mass loss as a primary metric for degradation. Laboratory experiments established proof-of-concept by demonstrating enhanced carbon mineralization, weight loss, and fragmentation of BMFs under bioaugmented conditions. These findings were translated to field-scale trials, where bioaugmentation treatments consistently outperformed untreated …

Meshed Trees: A Framework For Resilient Network Algorithms And Protocols, Peter Willis

Theses

The continued growth of computer networks in both size and complexity presents challenges for the control protocols that are tasked with maintaining optimal data-forwarding paths. These protocols commonly rely on shortest-path algorithms to determine where network data should be propagated and how it should be analyzed for inclusion in forwarding tables. However, problems arise during reconvergence, the process in which devices rediscover optimal paths following a network failure. Because control protocols were built decades ago for the networks of that era, the existing shortest-path algorithms utilized were designed for problems before the advent of modern computer networks. This resulted in …

Exploring Human Perception And Cognition In Expressing And Understanding Mechanical Designs, Yan-Ting Chen

Theses

Effective communication of mechanical designs through technical drawings requires geometric accuracy, efficiency, and an understanding of human perception and cognition. Although advances in computer-aided design (CAD) software have improved drawing precision and automation, current tools often overlook the spatial reasoning processes that users employ to interpret these representations. This study seeks to improve the accuracy and efficiency of human-computer interaction in CAD environments by examining how individuals perceive and interpret three-dimensional mechanical components within the context of technical drawings. A key focus is the identification of canonical and optimal views that align with intuitive human understanding. Through a series of …

Test Data: Raised Or Recessed? Finding The Optimal Gate Architecture For Improving The Static Performance Of Graphene Transistors, Ivan Puchades, Tzu-Jung Huang, Andrew Spencer, Luke Ingraham, Anibal Pacheco

Data

As silicon CMOS technology approaches its scaling limits, graphene offers a compelling alternative as the active material channel in transistors due to its high carrier mobility and atomically thin profile, which provide strong electrostatic control and promise high-performance analog applications. However, roadblocks such as device-to-device variation, high contact resistance, poor dielectric interfaces, and non-uniform graphene quality have limited the adoption of graphene field effect transistors (GFETs). Hence, further investigations are required for mitigating these issues at a material, e.g., by improving graphene transfer, and device level, e.g., by finding an appropriate gate architecture. In this work, we directly compare two …

Curriculum Insertion Proposal For The Academic-Military Education: The Rising Of Unmanned Aerial Systems (Uas/Drones) In Modern Combat, Tiago Marques Dos Santos Filho

Journal of Peace, Conflict, and Security Studies

The use of drones in the latest generation of combat has revolutionized military operations, offering new tactical and strategic-operational capabilities. Based on the author's practical experience and reference literature, using UAS in urban combat, peacekeeping missions, and jungle operations has proven to be extremely effective, providing significant advantages in terms of intelligence, surveillance, reconnaissance, and air support. Equipped with high-resolution cameras and advanced sensors, drones allow the collection of real-time critical information, assisting quick and accurate decision-making. This background raises the question of whether it is relevant to formally address this topic in academic-military undergraduation. The main hypothesis, that the …

Reforming Military Curriculum In The Era Of Big Data: Case Study Of The Albanian Armed Forces Academy, Etleva Smaci Assoc Prof

Journal of Peace, Conflict, and Security Studies

The digital revolution and the emergence of Big Data have profoundly impacted modern military operations. As data becomes a strategic asset, military education must evolve to prepare officers not only for traditional combat but also for data driven decision-making.

This case study explores how the Albanian Armed Forces Academy can reform its military curriculum to meet the demands of the Big Data era. The analysis is based on a review of contemporary literature and a survey conducted among students enrolled in the technology program at the Faculty of Defense and Security.

Findings indicate that students perceive the integration of big …

Military Academic-Scientific Production In Times Of Generative Ai: Ethical Boundaries And Challenges For Strategic Stability, Arlindo J. Barros Junior, Rômulo F. Santos, Weslei J. Batista

Journal of Peace, Conflict, and Security Studies

The adoption of emerging and disruptive technologies, which includes Artificial Intelligence (AI), has driven profound transformations across various sectors and in human behavior in recent years, permeating nearly all fields of knowledge. In this context, the use of AI as a tool to support academic-scientific production cannot be considered an exception. Additionally, there is a growing need for AI literacy for its users, for regulation and for the establishment of criteria to ensure these technologies are employed ethically and responsibly. In light of this global trend, the Brazilian Army has been seeking ways to regulate, manage, and optimize the use …

‘Reflective Learning’ – Teaching The South African Military Academy Way, Jean Pierre Scherman Dr

Journal of Peace, Conflict, and Security Studies

Professional military education for young officers within the South African National Defence Force (SANDF) has since 1950 been vested within the South African Military Academy (SAMA), Faculty of Military Science, Stellenbosch University. As an all services academy, the SAMA houses student from all four arms of service that constitute the SANDF, namely the South African Army, Navy, Air Force and Medical Health Services. With such a vastly different student body, the five schools within the SAMA correspondingly cover an extremely varied field of study ranging from military law and military management to military psychology all the way to more traditional …

Modernizing Military Education In Kosovo: From Theory To Practice Through Innovation And Technology, Linda Ziberi, Dardan Syla

Journal of Peace, Conflict, and Security Studies

This paper examines the need for Kosovo's Military Academy (KMA) to modernize its education system, particularly its necessity to transition from a theory-based methodology to more modern and innovative teaching and training approaches that incorporate advanced technology. Despite ongoing institutional development, the Kosovo Military Academy continues to rely on traditional teaching methods, which limits its capacity to prepare cadets for the demands of modern military operations. Barriers such as limited funding, outdated infrastructure, and resistance to pedagogical change further complicate efforts to modernize.

To address these challenges, the paper advocates for the adoption of modern, learner-centered strategies, including Simulation and …

The Greatest Victory: Teaching Strategy And Peace Through Negotiation, W. Chad Austin

Journal of Peace, Conflict, and Security Studies

This article examines how structured negotiation instruction, centered on the Circle of Value framework, enhances the critical and strategic thinking skills of cadets at the United States Air Force Academy (USAFA). Drawing on experiential learning, role-play simulations, and case studies—such as U.S.-China tensions over Taiwan—the article demonstrates how cadets apply integrative negotiation techniques to real-world geopolitical scenarios. The Circle of Value framework emphasizes interest-based negotiation, objective criteria, creative option generation, and the development of mutually beneficial outcomes. Through written analysis, live negotiation exercises, and reflective feedback, cadets build key competencies in communication, decision-making under pressure, and conflict resolution. The paper …

Language Alignment And Career Outcomes In International Military Education: A Study Of United States Military Academy Graduates, Erin Lemons

Journal of Peace, Conflict, and Security Studies

Host country/sending country language alignment is an understudied topic within the field of international military education. While individual-level language barriers are recognized, this study asks how national-level language proficiency levels can influence international military graduates’ retention. International cadets from countries with lower proficiency in the host nation’s language may be selected primarily for their language skills rather than their military potential. Moreover, the acquisition of the host nation’s language and culture during international cadets’ studies may increase the attractiveness of private-sector opportunities upon their return home. At the same time, countries with lower proficiency levels in the host language may …

Assessing, Selling And Onboarding Transformative Agreements At An R2 Institution​, Jennifer Freer, Daniel Trout

Presentations and other scholarship

Transformative agreements can help libraries expand content offerings and subsidize publishing costs. RIT Libraries, new to these agreements, has joined 4 over the past year in a process driven by Electronic Resources and Acquisitions/Serials. We will walk the audience through the assessment criteria for the two of the agreements we joined (Cambridge and Springer), along with lessons learned. The assessment criteria include: cost, impact on access to content, a scan of publishing activities on campus, as well as turnaway data obtained from vendors and a new implementation of Celus 5 for Counter 5 data.

We will share the language used …

The World Is Beautiful, Chelsea Demott Wildey

Theses

My thesis, The World is Beautiful is a short, digitally animated film that follows the journey of a jaded employee working at a dystopian fishery. The intention of this piece was to tell a well-paced, coherent story that also served as an allegory to spark verbal discourse in an audience. As a surface level story, the film portrays a working protagonist who has been forced to remain seated at her desk by a mechanical chair. She, presumably, has been monotonously pressing icons on a screen for her entire life until something catches her eye and prompts her to break free …

Advancing Applications Of Deep Learning On Network Traffic Analysis And Fingerprinting, Nate Mathews

Theses

The growing reliance on encrypted communication networks and privacy-preserving technologies, such as Tor, has intensified the demand for advanced defenses against traffic analysis attacks. Although encryption conceals content, the exposure of metadata—such as timing, packet size, and traffic volume—remains a significant vulnerability, allowing adversaries to infer private user behavior and visited websites. This dissertation addresses the limitations of existing analysis by advancing the application of deep learning techniques across multiple domains of traffic analysis and fingerprinting. The first major contribution is a comprehensive evaluation of current website fingerprinting defenses, revealing critical weaknesses against sophisticated modern attacks. Building on this foundation, …

Three-Dimensional Cfd Analyses Of Natural Circulation In A Pressurized Water Reactor During A Loss Of Coolant Accident, Arad Dehestany

Theses

In this research, ANSYS FLUENT simulations will be performed on natural circulation cooling performance during loss of coolant accident on the semi-scale Mod-2A geometry. Natural circulation experiments were performed in the semi-scale Mod-2A test facility which is a small-scale model of the primary system of a four-loop PWR nuclear power generating plant. The CFD results are validated using the tests done in the facility. The scope of the research is to understand the flow, temperature distribution, inventory coolant losses, and pressure drop in the system. These findings can provide insights into the performance of such systems and identify potential improvements …

From Waste To Wall Finish: Developing And Characterizing Sustainable Concrete Finishes With High-Volume Fly Ash And Biochar For Interior Applications, Prajwal Dudhane

Theses

This study explores the creation of environmentally friendly interior concrete finishes by recycling agricultural and industrial waste. In a 1:3 cementitious-to-aggregate mortar mix, the study investigates high-volume (30%) cement replacement using fly ash (FA30), biochar (BC30), and a hybrid combination (FAB30). It illustrates the viability of converting waste streams into workable architectural finishes through meticulous material investigation, mechanical testing, and aesthetic evaluation. Different performance characteristics were found by the technical examination. FA30 outperformed the control mix with a 14-day compressive strength of 8.00 MPa thanks to pozzolanic activity and decreased water demand. On the other hand, BC30 (7.33 MPa) significantly …

Examining Children’S Intuitive Understanding Of Mechanical Systems With A Gears Assembly Task, Nicole Taboada

Theses

Children’s causal reasoning about machines and their components is crucial for acquiring knowledge about science and math. Mechanistic understanding involves knowing how parts can be effectively connected to work together as a functional mechanical system. Little is known about how children’s understanding of mechanical systems develops across the lifespan. Legare and Lombrozo (2014) developed a gears assembly task to assess children’s understanding and learning of mechanics but did not track this skill across ages. The present study adapted the gears assembly task to measure mechanistic understanding in children between the ages of 4 to 11 years and adults. The goal …

Organizational Memories Of Extreme Events: Evidence From Us Public Transit Agencies, Mattia Caldarulo, Ignacio Pezo, Elizabeth A. Corley, Shaika L. Islam, Eric W. Welch

Articles

The increasing frequency and severity of extreme weather events require organizations to effectively manage the threats these phenomena pose. To respond to these challenges, public agencies often turn to their organizational memories for guidance. Organizational memories support information processing capacity, facilitate sensemaking, and legitimize and speed up decision-making processes. While memories influence different aspects of organizational life, little is known about their antecedents and the mechanisms behind the retrieval of past events. This study contributes to the broader literature on organizational memory by investigating the elements shaping public agencies’ retrieval of extreme weather events. Integrating weather data from the National …

Assessing The Feasibility Of Large-Scale, Selective Aqueous Quadrupole Ion Trap Separation, Daniel Brunner

Theses

The global challenges presented by water and resource scarcity and the drawbacks of the methods designed to resolve them escalate the need for innovative selective ion separation solutions. Environmental concerns, material constraints, high costs, and limited scalability are unavoidable disadvantages that hinder many selective separation technologies. Through its reliance solely on electric field manipulation and its avoidance of hazardous solvents or selective membranes, the quadrupole ion trap in an aqueous environment presents itself as a worthy alternative to contemporary separation methods. This research effort aims to gauge the feasibility of using a large-scale aqueous quadrupole ion trap (i.e. traps with …

Solar Power Forecasting Using Deep Learning Techniques, Fatma Abdulrahman

Theses

The growing utilization of solar energy and other renewable energy sources has heightened the demand for a proper forecasting model that enables efficient control of the energy supply as well as grid reliability. In this work, we concentrate about the use of novel techniques in ML models, namely Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), to try to forecast power output in a solar-powered plant using past weather and power output records. Production of solar energy is naturally volatile because it is dependent on the weather conditions and is problematic in nature when integrated into power grids. Conventional …

Illustrations For A Scientific Review Article Publication : Human Stem Cell-Derived Organoids, Sunghwan Bae

Theses

This thesis explores the role of scientific illustration in improving the comprehension of complex scientific concepts. It traces the historical development of illustrations in scientific literature and examines their functions in both research and review articles. The central contribution of this work is the development of twelve vector-based illustrations that elucidate the applications of human organoids within a review article context. These visuals transform intricate ideas into clear, engaging representations, supported by extensive research and verification to maintain scientific accuracy. The thesis concludes by addressing the future of scientific illustration, advocating for reader-oriented design approaches and the use of innovative …

Intelligent Monitoring And Alerting System Using Some Deep Learning Models, Omar Alshamsi

Theses

Road traffic crashes cause over 1.19 million fatalities per year worldwide and represent a major challenge for urban safety (World Health Organization, 2023; World Bank Group & WRI India, 2020). Smart city initiatives aim to use technology to reduce such losses through rapid accident detection and response (Arefin et al., 2025). This proposal outlines a vision for a Road Accident Detection and Response System that employs computer vision and deep learning to identify accidents from video feeds and immediately notify emergency services. The core of the system will be a custom-trained YOLOv8 object detection model, leveraging a dataset of annotated …

Democratizing Community Discourse Analysis In Computational Social Science, Md Towhidul Absar Chowdhury

Theses

Community resource inequities and undetected infrastructure vulnerabilities cost municipalities billions annually, with disproportionate impacts on marginalized communities. Current computational approaches to community needs assessment suffer from two critical limitations: they rely on aggregate-level analysis that obscures granular community expressions, and they implement sophisticated computational tools that remain inaccessible to stakeholders without technical expertise. This creates what we term the Community-Computational Gap—a persistent divide where domain experts with vital contextual knowledge cannot access the analytical tools they need, while computational experts develop models without sufficient community context. This dissertation addresses these challenges through a novel methodological framework for fine-grained utterance-level classification …

Enhance Telecom-Related International Indicators Using Machine Learning, Omar Alnemer

Theses

This thesis investigates the enhancement of the Network Readiness Index (NRI) through the application of machine learning methodologies to refine indicator weighting, clustering, and dimensionality. The study builds on research promoting data-driven methods to address the limitations of equal-weighted indices in capturing indicator importance and interdependence. The research aims to evaluate how unsupervised and supervised learning methods can optimize the interpretation of NRI data. The study focuses on three primary research questions: (1) How can PCA be used to reduce the dimensionality of the NRI without significant loss of information? (2) Can k-means clustering reveal meaningful groups of countries with …

Advancing Institutional Sustainability Through Green Roofs: Performance-Based Policy For Rit, Theoren Heilman

Theses

Utilization of green roof systems continues growth as a sustainable architectural strategy, offering enhancements to key building performance metrics while contributing to overall community resilience. The ability of green roofs to deliver a wide range of performance benefits, even in environments with harsh climatic conditions, positions them as an asset for advancing sustainable development. Within this context, university campuses represent an underutilized, yet important, setting for green roof adoption. Functioning much like small cities, campuses contain diverse building types and extensive infrastructure networks, which draw significant energy demands, positioning them to lead in sustainable building practices. Yet, most lack rigorous, …

Spectroscopy Pre-Trained Transformer (Specpt): A Universal Spectroscopic Analysis And Redshift Measurement Framework, Rohan Pattnaik

Theses

Spectroscopic surveys are essential for measuring galaxy redshifts and probing the physical processes driving galaxy evolution. As datasets grow in scale and complexity, traditional analysis methods face increasing limitations, motivating the development of scalable, data-driven alternatives. This thesis presents SpecPT, a transformer-based deep learning framework for general-purpose spectroscopic analysis, with a focus on redshift estimation. The model is first trained on DESI Early Data Release spectra from the Bright Galaxy and Emission Line Galaxy samples, jointly performing spectral reconstruction and redshift regression while learning a latent representation that captures the intrinsic properties of galaxies. SpecPT is then extended to a …