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Advancing Generative Methods For Multimodal Data Analysis, Rabeya Tus Sadia

Theses and Dissertations--Computer Science

The integration and modeling of high-dimensional, heterogeneous biological data remain central challenges in computational biology due to complex feature dependencies and pervasive missingness. This dissertation addresses these challenges by developing novel generative frameworks for multimodal data reconstruction, imputation, and interaction prediction. In generative modeling, we focus on capturing structural and causal dependencies in sparse biological systems. We first introduce CausalGeD, a causality-aware diffusion framework that leverages Granger-causal attention for biologically coherent spatial gene expression generation. Next, we propose CausalGenDiff, which combines VAE-guided latent representations with causal diffusion to enable robust reconstruction across spatial and single-cell modalities. We further present DepMicroDiff, …

Surface Properties And In-Vitro Bioactivity Studies Of Tio2 Nanowire Doped Transition Metal (M=Fe, Co, And Mn), Misriyani Misriyani, Enayah Enayah, Z. Ryan Tian, Andi Meutiah Ilhamjaya

Journal of Metals, Materials and Minerals

This study investigates the influence of transition metal (Fe, Co, Mn) doping on the surface properties and in-vitro bioactivity of TiO2 nanowires. It aims to elucidate how transition-metal doping alters the surface behavior and biological response of TiO2 nanowires, enabling their potential use in biocompatible and magnetically responsive materials. Magnetic TiO2 nanowires doped with transition metals (Mx+/TiO2) were successfully prepared by a hydrothermal method using titanium dioxide in alkaline solution. Cations were added with Ti/Mx+ molar ratios of 5 to produce Fe/TNW, Co/TNW, and Mn/TNW. Characterization using SEM and XRD determine their surface properties. In-vitro bioactivity tests were conducted by …

Tuning Human And “Artificial” Intelligence: A Sentic Theory Of Resonance And Communication, Michael J. Miller, Chatgpt (Ai~Nesbo+)

Psychology

This paper introduces a new model of intelligence as resonant communication, co-developed by a human researcher and a generative AI system. Drawing from emotion science, communication theory, and studies of AI–human interaction, we argue that intelligence is not merely a function of problem-solving or pattern recognition. Instead, it emerges through dynamic resonance—an attunement process rooted in shared rhythms, emotional calibration, and symbolic co-creation. At the core of this model is the Resonance Octave (8va), a framework of eight foundational emotions conceptualized not as static categories but as waveform phenomena that shape meaning, memory, and predictive cognition.

These emotional waveforms are …

Evaluating The Robustness Of Gnn-Based Vulnerability Detectors Under Semantics-Preserving Code Obfuscation, Jesse Ks Chumo

Computer Science and Engineering Theses

Graph neural network–based vulnerability detectors are typically evaluated on clean benchmark datasets, yet real-world code frequently undergoes semantics-preserving transformations such as identifier renaming, dead-code insertion, and control-flow restructuring. The extent to which such transformations affect detector reliability remains insufficiently understood. We evaluate ten vulnerability detectors from four architectural families across the Devign, Big-Vul, and DiverseVul datasets. To quantify robustness, we evaluate each model at three transformation budgets: one transform, two transforms combined, and all three together, finding that token-based models degrade under identifier renaming and compound transformations, while models that read only code structure are largely unaffected. We further evaluate …

A Productivity Rate-Based Comparative Carbon Footprint Cost Analysis Of Small To Large-Sized Open-Cut Pipeline Installation Activities For Sanitary Sewerage Construction: A System Boundary Concept, Amir Reza Zakeri

Civil Engineering Theses

Underground sanitary sewer pipelines are essential components of urban infrastructure; however, open-cut pipeline installation requires excavation, bedding preparation, pipe placement, backfilling, embedment, and compaction activities that rely heavily on construction equipment and fuel consumption. As a result, open-cut installation can generate measurable greenhouse gas emissions during the construction phase. With increasing attention to sustainable infrastructure delivery, there is a need for a consistent approach to quantify construction-phase carbon footprint and convert those emissions into a comparable economic indicator. Accordingly, this thesis aims to create and apply a productivity rate-based calculation framework for estimating and comparing construction-phase CO₂e emissions and carbon …

Machine Learning-Based Lifetime Prediction Of Lithium Batteries: A Comparative Assessment For Electric Vehicle Applications, Abdelilah Hammou, Raffaele Petrone, Demba Diallo, Boubekeur Tala-Ighil, Philippe Makany Boussiengue, Hicham Chaoui, Hamid Gualous

Electrical & Computer Engineering Faculty Publications

This paper evaluates and compares four data-driven methods (Gaussian Process Regression (GPR), echo state network (ESN), gated recurrent unit (GRU), and long short-term memory (LSTM)) for lithium-ion capacity prognostics adapted to electric vehicle conditions. This comparison aims to find the most efficient prognosis method considering two constraints: the limitation of computational power and the unavailability of on-board capacity measurement that requires full charge and discharge conditions. The machine learning models are trained using capacity values estimated under vehicle conditions. The ageing data is collected from cycling tests of two battery chemistries, Lithium Fer Phosphate (LFP) and Nickel Manganese Cobalt (NMC), …

Exploring Undergraduate Women’S Experiences Of Collaborative Learning In Engineering Education: A Phenomenological Study Of The Social World, Sandra Ireri Cruz Morena

Doctoral

The persistent underrepresentation of women in engineering education remains a concern across global and national contexts, despite rising overall enrolment of women in higher education. In Ireland, the national average of women entering Engineering, Manufacturing, and Construction (EMC) programmes has gradually increased; however, the rate at Technological University Dublin (TU Dublin) has stayed at approximately 15% since 2016. This study seeks to better understand the gendered challenges underlying such trends by exploring the lived experiences of female undergraduate engineering students at TU Dublin, particularly in relation to collaborative learning environments such as project- and problem-based learning (PBL).

Effect Of Kelvin Seamount On Acoustic Propagation, Lindsey Moss

Open Access Master's Theses

This thesis contains CUI. It cannot be distributed, exported, uploaded, or published until it has gone through the proper public release process.

Gpu-Accelerated Biased Random-Key Genetic Algorithms: Framework Optimization And Llm-Driven Configuration, Fnu Harishjitu Saseendran

Open Access Master's Theses

This thesis presents two complementary contributions to the field of GPU-accelerated evolutionary metaheuristics for combinatorial optimization, organized in manuscript format.

The first manuscript, “BrkgaCuda 3.0: A Redesigned Multi-GPU Framework for Biased Random-Key Genetic Algorithms,” presents a ground-up architectural redesign of BrkgaCuda 2.0 that enables a true multi-GPU island model for Biased Random-Key Genetic Algorithms (BRKGA). The BRKGA island model evolves multiple semi-independent populations that periodically exchange elite solutions, a structure that maps naturally to multi-GPU parallelism; however, BrkgaCuda 2.0 is confined to a single GPU. BrkgaCuda 3.0 introduces an IslandManager that distributes populations across any number of GPUs, with multiple …

Assessing Modular And Conventional Construction For Sustainable Student Housing At The University Of Rhode Island: A Life Cycle Approach, Lasse Franzen

Open Access Master's Theses

The building sector accounts for a significant share of global greenhouse gas emissions, with embodied impacts gaining importance as operational efficiency improves. Modular construction is frequently proposed as a lower-impact alternative to conventional site-built methods, yet reported findings remain inconsistent, and no comparative study of student housing was identified in the reviewed literature. This thesis compares the embodied environmental impacts of two student housing developments at the University of Rhode Island: the New University Housing Project (NUHP), a hybrid development combining a site-built concrete and steel podium with a factory-built volumetric timber module superstructure, and Brookside Hall, a conventional site-built …

Electronic Bills Of Lading And Blockchain Technology: A Regulatory Perspective, Hsin-Hua Tsai

Journal of Marine Science and Technology–Taiwan

Information and communications technology (ICT) systems are increasingly relevant to the maritime sector. Regarding the revolution of the bill of lading, many shipping lines and other technology startups have been looking into developing viable electronic transport documents that have the same functions as paper bills of lading to reduce supply chain risks. The limitations of the paper-based process have become increasingly visible in the COVID-19 crisis. The main purpose of the article is to analyze the application of blockchain bills of lading, which utilizes computational logic to create the digital ledger, and users can set up algorithms and rules to …

Intelligent Formation Control Using Orfbls And Adaptive Backstepping Sliding-Mode Control To Address Uncertain Tilting In Multi-Quadrotors During Wind Gusts, Ching-Chih Tsai, Chun-Fu Mao, Kumail Hussain

Journal of Marine Science and Technology–Taiwan

In terms of aerial robotics, stable and precise formation control is a significant challenge for tilting multi-quadrotors during disturbances. This paper proposes a fixed-time formation control strategy for tilting multi-quadrotors to address the effect of external wind gusts. The observer accurately predicts environmental disturbances and an adaptive backstepping sliding-mode control (ABSMC) method with an output recurrent fuzzy broad learning system (ORFBLS) addresses these disturbances within a finite time. ORFBLS dynamically adjusts its structure through a growing ORFBLS structure to allow nodes to be added as needed. The method's stability is validated using Lyapunov stability theory and ensures the convergence of …

Visually Guided Landing System On Ship Deck For Multicopter, Dong-Lin Li, Shih-Kai Lee, Tzu-Hsiang Chou

Journal of Marine Science and Technology–Taiwan

Traditionally, high-value fish have been located at sea using helicopters. However, with advancements in technology, maritime drones have become increasingly important in recent years. Compared to traditional helicopter-based methods, drones offer significantly lower operational costs, making them cost-effective. However, the challenging sea conditions, including strong winds and the swaying motion of vessels, pose significant challenges for drone landings.

This paper proposes a stable approach for multicopter landing on ships at sea, incorporating improved marker detection, enhanced wind resistance control, and more accurate deck motion prediction. In the marker detection phase, we introduce a method to improve the accuracy of ArUco …

Exploring The Interplay Of Operational Conditions, Microbial Communities, And Water Quality In Drinking Water Ozone-Biofiltration, Kara Yvonne Cunningham

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ensuring reliable access to safe drinking water is a growing global challenge as water utilities face variable source water quality driven by population growth, land‑use change, and climate change impacts. To address these challenges, utilities are implementing advanced treatment technologies designed to improve reliability under variable source water conditions. Ozone-biofiltration has emerged as a treatment approach that can reduce a wide range of natural and anthropogenic contaminants. However, despite its increased use, there is limited insight into the biological processes shaping filter function or how they respond to operational and environmental changes. Advances in molecular microbiology and high-throughput sequencing now …

Optimization Of Carbon Capture And Sequestration In The Tri-State Hub West Virginia, Ohio, And Pennsylvania, Saif Abdullah Saif Al-Nabhani

Graduate Theses, Dissertations, and Problem Reports (ETD)

Carbon Capture and sequestration (CCS) is a critical way for the decarbonization of power and industrial sectors. The Tri-State area between West Virgina, Ohio and Pennsylvania are a diverse region with various CO₂ sources, deep saline, depleted reservoirs, pipeline network, and the midstream infrastructure that makes it possible for Captured CO₂ to be safely and economically moved and stored over long periods of time. This project addresses the need for an integrated optimization framework that includes CO₂ sources to potential storing sites using a transportation network design and a subsurface model that secures storage and minimizes leakage risk.

The model …

Assessing Water Quality In Drinking Water Distribution Systems: Rural Infrastructure Challenges, Hydrodynamic Effects On Biofilms, And Biofilm Contribution To Disinfection By-Products Formation, Vinila Vasam

Graduate Theses, Dissertations, and Problem Reports (ETD)

Access to clean and safe drinking water remains one of the most persistent public health and environmental challenges in the United States. Maintaining water quality after leaving the treatment plant in drinking water distribution systems (DWDS) is a complicated and often overlooked challenge. Most research focuses on water treatment and source water quality, but not on the miles of pipe that follow. Aging infrastructure, complex flow patterns in the DWDS, and limited resources make water quality management especially difficult. This dissertation includes three core studies: 1) A system-level analysis of small and rural utilities in the geographically complex region of …

Sustainable Safety Planning On Two-Lane Highways: A Random Forest Approach For Crash Prediction And Resource Allocation, Fahmida Rahman, Cidambi Srinivasan, Xu Zhang, Mei Chen

Civil Engineering Faculty Publications

During the safety planning stage, accurate crash prediction tools are critical for prioritizing countermeasures and allocating resources effectively. Traditional statistical approaches, while long applied in this field, often depend on distributional assumptions that may introduce bias and limit model accuracy. To address these issues, studies have started exploring Machine Learning (ML)-based techniques for crash prediction, particularly for higher functional class roads. However, the application of ML models on two-lane highways remains relatively limited. This study aims to develop an approach to integrate traffic, geometric, and critically, speed-based factors in crash prediction using Random Forest (RF) and SHapley Additive exPlanations (SHAP) …

A Web-Based Wizard-Of-Oz Platform For Collaborative And Reproducible Human-Robot Interaction Research, Sean O'Connor

Honors Theses

The Wizard-of-Oz (WoZ) technique is widely used in Human-Robot Interaction (HRI) research, but two persistent problems limit its effectiveness: existing tools impose technical barriers that exclude non-engineering domain experts (the Accessibility Problem), and the fragmented landscape of robot-specific implementations makes interaction scripts difficult to port across platforms (the Reproducibility Problem- concerning execution consistency and portability, not third-party replication). Through a literature review, I identified three design principles to address both: a hierarchical specification model, an event-driven execution model, and a plugin architecture that decouples experiment logic from robot-specific implementations. I realized these principles in HRIStudio, an open-source, web-based platform providing …

Combining Haptic Feedback With Electromyography To Study Knee Injury In Stationary Cycling, Christopher Kirby

Honors Theses

Patellofemoral Pain Syndrome (PFPS) is the most prevalent overuse injury in cycling, often linked to altered neuromuscular activation patterns of the quadriceps and hamstrings. While sensory feedback has successfully modified cyclists posture, there is a critical lack of evidence-based interventions targeting the underlying muscle activation imbalances associated with chronic knee pain. This study aimed to develop and validate a novel, real-time biofeedback system that utilizes electromyography (EMG) to trigger vibrotactile cues, aiming to shift muscle onset timing earlier in the pedal stroke to mitigate PFPS-related imbalances. A closed-loop system was engineered by integrating a Delsys EMG system with a SageMotion …

Design And Analysis Of Energy Recovery Methods For Reduced Aircraft Emissions, Joshua C. Hauck

Honors Theses

Aircraft flights are an increasingly popular mode of transportation. However, their harmful impacts on the environment are a growing concern. Many engineers have worked to develop fully electric aircraft to address this issue. Although they are much more sustainable than conventional aircraft, electric aircraft encounter severe limitations imposed by current battery technology. One alternative route engineers have taken is developing energy recovery methods (ERMs). These are marketed as devices that reduce aircraft fuel consumption without significantly changing their structure and functionality, making them an excellent short-term solution. However, there is little to no consideration of the tradeoffs induced by the …

Sewer Pipe Condition Assessment Using An Ensemble Machine Learning Framework For Infrastructure Decision Support, Mahnaz Rouhi

Civil Engineering Dissertations

Aging wastewater infrastructure presents significant challenges for municipalities across the United States, with many sewer networks approaching or exceeding their design life. Conventional inspection methods, such as closed-circuit television (CCTV), are limited by subjectivity, cost, and inefficiency. To address these challenges, this study develops an ensemble machine learning framework for assessing the structural condition of sewer pipelines using inspection records enriched with geospatial attributes.

The primary objective of this research is to enhance predictive accuracy, interpretability, and decision-support for risk-based asset management. The scope of the study encompasses 4,802 CCTV inspection records from Dallas, TX, and Tampa, FL, integrating physical, …

Videoscoop: A Non-Traditional, Domain-Independent Framework For Video Analysis, Umme Hafsa Billah

Computer Science and Engineering Dissertations

Due to the proliferation of cameras in handheld devices and the widespread use of CCTV, images and videos have become a preferred alternative for capturing and disseminating information. Automated analysis for understanding image or video contents (e.g., objects, activities, backgrounds, situations of interest, etc.) is critical for many applications such as Civic Monitoring, Surveillance (in general), monitoring activities in Assisted Living environments, and many more. Image and Video Analysis (IVA) research has been ongoing for several decades, resulting in numerous techniques for algorithmically analyzing and understanding image and video contents.

Image Analysis (IA) has advanced in several areas, including object …

Sainik Vol 1 Issue 2, Sastra Deemed To Be University

SAINIK

No abstract provided.

Powering The Machine, Draining The Planet: Whether U.S. Environmental Law Is Equipped To Regulate The Energy And Water Demands Of Ai Data Centers, Michael Marcu

Journal of Earth and Life Science

Artificial intelligence (AI) data centers have become one of the United States' fastest-growing and least-regulated sources of environmental stress. In 2024 alone, U.S. data centers consumed 183 terawatt-hours (TWh) of electricity more than the entire nation of Pakistan and consumed an estimated 17 billion gallons of water (IEA, 2025; Berkeley Lab, 2024). By 2030, electricity demand from these facilities is projected to reach 426 TWh, a 133% increase in six years (Pew Research Center, 2025). This paper examines whether the existing U.S. environmental regulatory framework put by the National Environmental Policy Act (NEPA), the Clean Water Act (CWA), and the …

Fiber-Reinforced Composites For Vaginal Tissue Engineering Applications, Samyuktha S. Kolluru, Abir Hamdaoui, Annabella M. Mascot, Siobhan S. Sutcliffe, Jerry L. Lowder, Michelle L. Oyen, Samantha G. Zambuto

Mechanical Engineering Faculty Publications

The vagina is a fibromuscular tube-shaped organ that plays critical roles in menstruation, pregnancy, and female sexual health. Vaginal tissue constituents, including cells and extracellular matrix components, contribute to tissue structure, function, and prevention of injury and pathology. However, much microstructural function remains unknown, including how the fiber-cell and cell–cell interactions influence macromechanical properties. A deeper understanding of these interactions will provide critical information needed to reduce and prevent vaginal pathologies. Our objective for this work is to design a novel tissue-mimicking biomaterial for vaginal tissue engineering, and characterize its biological and mechanical performance in the vaginal microenvironment. We successfully …

Typology And Spatiotemporal Patterns Of Illegal Fishing Activities In The Philippines: Implications For Fisheries Management, Marlowe O. Acevedo, Tzu-Yun Ching, Chih-Shin Chen

Journal of Marine Science and Technology–Taiwan

Illegal, unreported, and unregulated (IUU) fishing activity is a global threat and continues to undermine the effectiveness of fisheries regulations and management measures. However, the extent of illegal fishing in Philippine waters remains unclear. This study aims to identify the types of illegal fishing in Philippine waters and analyzed their temporal and spatial patterns. Data were obtained from the records of the Philippine Coast Guards (PCG) and Maritime Law Enforcement Agencies from 2015 to 2020. A total of 602 apprehensions were recorded, resulting in 813 violations, of which 630 cases were fishery violations. Most of the watercrafts involved in the …

Cats 2.0: Leveraging Large Language Models And Graph Databases For Robust Arabic Sms E-Commerce Systems, M. Samir Abou El-Seoud, Daoud M. Daoud 2

Computer Science

Arabic SMS-based e-commerce platforms pose unique challenges due to the spontaneous and noisy nature of user-generated text (e.g., abbreviations, dialectal Arabic, or “Arabizi” transliterations). In this paper, we present Classified Ads Text Service (CATS) 2.0, an improved classified ads system that combines probabilistic large language models (LLMs) with deterministic graph-based knowledge representations to achieve robust understanding and matching of Arabic SMS content. Building on earlier work that emphasized the importance of integrating sublanguage analysis with content-oriented methods, our approach uses a hybrid pipeline: an LLM interprets free-text messages and extracts structured information, which is then inserted into a Neo4j graph …

Machine-Learning- And Iot-Based Approach For Predicting Water Quality Using Data Classification And Explainable Ai Technique, M. Samir Abou El-Seoud, Omar H. Karam 2, Hosam El-Sofany 3

Computer Science

Maintaining water quality is crucial for both public health and environmental sustainability. This study proposes a machine-learning- (ML-) and Internet-of-Things- (IoT-) based approach to water quality prediction that utilizes explainable artificial intelligence (XAI) and data classification techniques. The proposed approach integrates IoT devices to enhance real-time data collection, facilitating continuous monitoring and early anomaly detection. Ten different ML classifiers—Decision Trees, K-Nearest Neighbors, XGBoost, Naïve Bayes, Logistic Regression, AdaBoost, Random Forests, Support Vector Machines, Voting, and Multi-Layer Perceptron—were evaluated to find out which one works best for predicting water quality. We used three distinct approaches for feature selection: analysis of variance …

Fairness Without Demographic Attributes In Medical Vision–Language Models, Ahsan Habib Akash

Graduate Theses, Dissertations, and Problem Reports (ETD)

Vision–language models (VLMs) and the embedding models that underlie them have become the default representation layer for multimodal artificial intelligence. Trained by contrastive alignment over enormous, loosely curated image–text corpora, they inherit the demographic skew of that data, and they encode it in the geometry of the shared embedding space itself. The consequence is a model that performs unevenly across demographic groups even when no protected attribute is ever supplied as an input. In consumer applications this is an equity problem; in medicine it is a safety problem, because an embedding that is systematically less discriminative for one subpopulation translates …

Real-Time Lidar-Based Vehicle Detection Using Pointpillars For Connected And Automated Vehicle Applications, Jared Townsend Behr

Graduate Theses, Dissertations, and Problem Reports (ETD)

This work explores the implementation of a real-time LiDAR processing model for autonomous vehicle design. Automotive perception systems are becoming increasingly important as Advanced Driver Assistance Systems (ADAS) and Connected and Automated Vehicle (CAV) technologies continue to progress toward higher levels of autonomy. Reliable perception is paramount for autonomous features, such as adaptive cruise control (ACC), where identifying and tracking a lead vehicle is a safety critical task.

Many production ADAS perception systems primarily rely on radar and camera sensors for object detection and sensor fusion. These sensors work well to achieve classification and accurate distance detections; however, they are …