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Modeling And Autonomous Control Systems For A Delivery Drone Application, Dana Helal Alnuaimi

Theses

This thesis focuses on the development of a multi-drone navigation and control system, aiming to enhance payload capacities beyond the limits of single-drone systems. By integrating multiple drones to work collaboratively as a unit, this study addresses the challenges associated with lifting and transporting heavier payloads.

The primary objective is to design and evaluate a multi-drone system capable of working in tandem to transport larger payloads efficiently. The research aims to develop robust control algorithms, supported by system identification for dynamic modeling, and navigation strategies to enable effective coordination between drones.

The study employs a combination of simulation and real-world …

Study Of The Effect Of Biodiesel Derived From Jojoba Oil With Alcohols Blends On Diesel Engine Performance, Exhaust Emissions, Vibration, And Noise, Yassir Abdelrahman Elbashier

Theses

This study presents a mutual investigation on the properties of the fuels and the performance of an engine using biofuels from mixtures of jojoba oil biodiesel with alcohols. The work consists of mainly two phases, examining the properties of the jojoba biodiesel-alcohols mixtures and the performance and emission behavior in a single piston diesel engine. A base mixture of 50% jojoba biodiesel and 50% diesel produced, and this was fractionally mixed with 5, 10, and 20% methanol and with 5, 10, and 20% diethyl ether (DEE). The rheological properties namely viscosity and shear stresses of all biodiesel blend mixtures were …

Advancement And Characterization Of Next-Generation Solid-State Photon-Counting Image Sensors For Astrophysics Applications, Nicholas R. Shade

Dartmouth College Ph.D Dissertations

Astronomers’ pursuit of detecting light from increasingly faint and distant objects in the expanse of space necessitates continuous improvement in signal-to-noise ratio of camera technology. Recent advancements in solid-state detector technologies have enabled the determination of photon-number, including single photon events, enabling observations at the fundamental limits of physics. These developments are instrumental not only for standard two-dimensional imaging but also for advanced spectroscopy, which increasingly drives future astrophysical applications. This thesis presents an evaluation of three next-generation silicon-based detectors capable of photon-counting with deep-sub-electron input-referred read noise: the electron-multiplying charge-coupled device (EMCCD), the single-photon avalanche diode (SPAD), and the …

A Low-Noise And High-Gain Integrated Photoplethysmography Sensor For Continuous Vital Signs Monitoring, Neethu Mohan

Dissertations

Photoplethysmography (PPG) sensing is an important technology used for measuring health parameters like, heart rate, respiratory rate, blood oxygen saturation, and blood pressure (BP). The PPG sensing is used for individuals who have to periodically monitor their health due to chronic health conditions. The basic requirements of a wearable PPG sensor include non-invasiveness, prolonged battery life, and being userfriendly. These type of sensors have great demand in the healthcare applications and there is a significant rise in the demand of these sensors. The basic objective of these PPG sensors is to make the continuous vital health monitoring easier without the …

A Comparative Study On Performance Of Iot-Driven Ml-Enabled Forecasting Models For Efficient Air Quality Monitoring, Bara Ksiksi

Theses

Air pollution is one of the most critical environmental challenges affecting public health globally, responsible for approximately 4.2 million premature deaths annually according to the World Health Organisation. This thesis presents a comparative study of IoT-driven machine learning forecasting models for air quality monitoring in Abu Dhabi, UAE, introducing a zonal approach combined with satellite-based spatial validation. The primary objective is to evaluate forecasting performance across three distinct activity zones using ground station data from the Environment Agency Abu Dhabi (EAD), and to incorporate a spatial validation component using satellite imagery to assess the consistency of ground-based predictions at a …

Development Of A Benchmark Building Condition Index Utilizing Discrete Facility Subsets For Use In Risk Prioritization Analysis, Christopher A. May

Engineering Management & Systems Engineering Theses & Dissertations

Within the healthcare facilities management arena, key performance-based condition indices such as a calculated Building Condition Index (BCI) are currently utilized as a governing indicator of facility health and performance. However, BCI alone does not adequately support enterprise-level risk prioritization and fails to provide a validated facility-to-facility risk prioritization model. Assets within the same enterprise receiving similar sustainment funding experience different rates of degradation depending on asset type and construction age thus impairing the BCI rating scale. Statistical analysis of facility metrics indicates a strong correlation between facility degradation drivers and prediction of a subset-based benchmark BCI. The research validates …

Observations Of An Oscillatory Mechanochemical Reaction Between Tetrathiafulvalene And Chloranilic Acid, Alastair Deans

Physics Theses & Dissertations

Mechanochemistry is the study of chemical reactions driven by the input of mechanical en ergy in addition to thermal activation. Mechanochemical reactions from powders are carried out by manual grinding or milling using various types of ball mills, or in twin extruders. While mechanochemistry has great potential affording economically and environmentally advantageous “green” synthetic methods, a drawback is that its chemical mechanisms are not well understood. One example of such a reaction currently under study involves tetrathiafulvalene, an organic elec tron donor with two polymorphs (orange and brown), and chloranilic acid, an electron acceptor. Previous results show that neat grinding …

Sustainability In Concrete: Decision-Makers, Dismissal Points, And A Framework For Implementation, Max Dennison

Construction Management

Concrete is essential to modern infrastructure, but is also one of the largest sources of embodied carbon, with cement production alone responsible for a significant share of global CO₂ emissions. Although low-carbon and otherwise “sustainable” concrete technologies are growing, their use in everyday projects remains limited. This research investigates why sustainable concrete options are most often dismissed during the project lifecycle, who drives these decisions, and what conditions are needed to enable broader adoption. Using a combination of literature review and semi-structured interviews with professionals in contracting, life-cycle assessment, sustainability consulting, and materials production, the study maps decision points from …

Aiw26s: Machine Learning Of Structured Data, Moumita Saha

Paul English Applied Artificial Intelligence (AI) Institute Publications

This workshop introduces the fundamentals of machine learning for structured data, focusing on tabular datasets and real-world applications. Participants explore key concepts such as data types, data preprocessing, feature engineering, and supervised learning methods. The session covers commonly used models, including linear regression, logistic regression, decision trees, and neural networks, along with evaluation metrics such as RMSE, accuracy, and confusion matrices. By the end of the workshop, participants will have gained a practical understanding of how to build, interpret, and evaluate machine learning models for structured data.

An Integrated Bayesian Network-Based Zero Trust Model To Quantify Cyber Risk In Small-Medium Businesses, Ahmed Abdelmagid

Engineering Management & Systems Engineering Theses & Dissertations

Small-medium businesses (SMBs) play a pivotal role in the worldwide economy as they constitute the most considerable portion of businesses in developed countries like the UK and the US. As such, SMBs are likely targets of cybercrimes by malicious agents because of their vulnerable IT systems. The digital infrastructure of SMBs is more likely to be hit by cyberattacks than large businesses due to many factors that facilitate hackers’ missions. These factors include a limited financial budget devoted to cybersecurity, a lack of knowledge, an underrating of how dangerous cyber threats are, and a shortage of IT expertise. The enormous …

Bridging Mission And Execution: Integrating Participatory Design In Early-Phase Mission Engineering For Stakeholder Alignment And Mission Clarity, Rafi Soule

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation develops and evaluates an integration-centered approach to early-phase Mission Engineering that improves mission clarity under ambiguity. Stakeholder interpretations diverge, and interoperability constraints are not surfaced early. These conditions reduce mission clarity and weaken mission-to-system mapping readiness. The dissertation proposes an integration-centered approach that strengthens early mission framing through two complementary mechanisms: (1) a participatory design-inspired, artifact-first workflow that surfaces and repairs interpretation divergence, and (2) closed-corpus, RAG-enabled retrieval that grounds mission-to-system mapping in traceable evidence. The study was organized around a construct spine linking shared understanding, stakeholder alignment, and interoperability feasibility to mission clarity. A three phase mixed-methods …

Cavitation-Aware Design Of Hydrofoil Sections For Marine Propeller Blade Development, Samuel G. Bacon

Mechanical & Aerospace Engineering Theses & Dissertations

Cavitation is a major design constraint for marine propeller blade sections because it can reduce hydrodynamic performance, increase vibration and noise, and contribute to surface damage. This thesis develops and applies an exploratory computational framework for cavitation-aware hydrofoil-section design relevant to marine propeller blade development. The framework combines section-level CFD validation, CST-based geometry parameterization, pressure-based pre-screening, matched-load comparison, and focused predicted inception envelope or cavitation-bucket analysis.

The CFD methodology was validated against published YS-920 hydrofoil water-tunnel data using selected fully wetted, near-inception, and cavitating reference cases. The validation results showed that the adopted framework reproduced the key experimental trends needed …

Biocrude From Organic Waste And Its Conversion To Hard Carbon: Experimental And Modeling Study, Isamu Umeda

Civil & Environmental Engineering Theses & Dissertations

This study establishes a technical and theoretical foundation for the efficient conversion of organic waste into biocrude and high-value carbon materials, aiming to facilitate the industrialization of hydrothermal and solvothermal liquefaction. The dissertation research is structured as follows:

Chapter 2 developed a novel chemical kinetic model for the HTL of corn stover based on elemental balances (C, H, N, and O). By incorporating temperature, residence time, solid loading as an independent variable, the model successfully predicted product yields and properties, revealing that there was non-pseudo-first-order reaction pathways in the conversion of water soluble organics in aqueous phase (AP) to hydrochar. …

Engineering Cryogenic Thermal Links And Transport Systems For Conduction-Cooled Superconducting Cavities, Jacob B. Lewis

Mechanical & Aerospace Engineering Theses & Dissertations

The Thomas Jefferson National Accelerator Facility (Jefferson Lab) is currently developing a prototype conduction-cooled 915 MHz SRF cryomodule proposed for industrial use, capable of increasing the energy of an electron beam with 5 mA current by ~ 4 MeV. Two Nb3Sn resonant cavities are under development for this project, in which cryogenic cooling is provided by closed cycle refrigerators (cryocoolers). One cavity utilizes high-purity electroformed copper on the outer surface to provide heat extraction from the cavity, the other relies on high-purity aluminum thermal links. This thesis investigated the thermal conduction pathways between the cavities and cryocooler cold heads, with …

Tuning And Performance Of Pid Controlled Low Complexity Systems, Timothy Evans

Honors Theses

Proportional integral derivative (PID) controllers are used for precise position and orientation control in systems such as autonomous underwater vehicles (AUVs). This project supports the University of Southern Mississippi’s (USM) Robotics Club’s RoboSub AUV effort by developing, troubleshooting, and manually tuning PID controllers to characterize tracking performance and settling time across systems of increasing complexity. Initially, the project hypothesized that tracking performance would be reduced and settling times would increase as system complexity advanced from one degree-of-freedom (DOF) to two DOF. However, prior research was found that suggests that for small disturbances around an equilibrium state, separate PID-controlled DOFs can …

Bio-Payload Senior Design Report, Connor Bishop, Oliver Goodall, Marcus Kirk, Gabby Robles, Anish Shanmuganathan

Interdisciplinary Design Senior Theses

This project focuses on the design and development of an autonomous experimental platform capable of conducting cellular biology experiments in a well plate within a CubeSat environment. The system integrates microfluidics, robotics, and onboard sensors to remotely initiate experiments, monitor them, and collect data without human intervention. The objective is to create a platform for automated biological experimentation in microgravity, while reducing reliance on ground-based control and increasing mission efficiency and reproducibility. The team used Saccharomyces cerevisiae to assess the biocompatibility of the well plate and monitor changes in cell culture, including optical density and cell viability.

Engineering Exosome Delivery Systems For Targeted Cancer Therapeutics, Gerardo Aguayo Quezada, Mahika Arya, Eduardo Noyola Mojarro

Bioengineering Senior Theses

Treatments for glioblastoma (GBM) are limited, mainly because the blood-brain barrier (BBB) prevents large molecules like chemotherapeutic drugs from reaching brain cells, and other methods like brain surgery are incredibly invasive. Brain surgery is useful for large masses of tumors, but the surgery can’t always remove the entire tumor, which is where radiation can be used, but only in limited quantities to prevent neural damage. To circumvent these gaps in modern medicine, exosomes, which are naturally secreted nanoparticles, offer an exciting way to deliver treatments to diseased cells. Exosomes biologically cross the BBB and transport materials between cells. In our …

Comparative Analysis Of Traffic Impact Study Accuracy Using Turning Movement Volume Counts., Kathryn Riopel

Master of Engineering Theses

Traffic forecasting and modeling has been a significant subject of debate within the transportation sector as of the last decade. Transportation agencies and planners use traffic forecasting and modeling in order to predict current and future transportation needs, as well as the impacts of proposed developments. In particular, state departments of transportation (DOTs) and city level agencies often require developers to conduct Traffic Impact Studies (TISes) in order to gauge necessary transport network enhancements to handle new demand from proposed developments. The standards by which these TISes are conducted and judged varies widely, but primarily consists of existing traffic counts, …

Efficiency Comparison Of Reduced Graphene Oxide (Rgo) Composite-Incorporated Polyacrylonitrile Nanofibrous Filters For Respirable Crystalline Silica Dust And Coal Dust, Mahsa Moradi, Ashish Kakoria, Lina Zheng, Guang Xu

Mining Engineering Faculty Research & Creative Works

The health of miners working in underground mines is greatly threatened by their exposure to respirable crystalline silica (RCS) found in coal dust. While coal dust includes RCS, it is important to know the specific filtration efficiency for RCS particles compared to coal dust to improve protective measures. This study compares the filtration efficiency of reduced graphene oxide (rGO) composite-incorporated Polyacrylonitrile (PAN) nanofibrous filters at four different concentrations of rGO (0, 2, 6, and 10 wt.%) for RCS particles and coal dust. The filters were made using the electrospinning method. They were tested separately with RCS particles and coal dust …

Deep Learning-Based Structural Displacement Identification And Quantification Under Target Feature Loss, Lishuai Zhu, Guangcai Zhang, Qun Xie, Zhen Peng, Li Ai, Ruijun Liang, Taochun Taochun Yang

Civil Engineering Faculty Publications

Structural displacement monitoring faces significant challenges under complex environmental conditions due to the loss or degradation of target features, making it difficult for traditional methods to ensure high accuracy and robustness. Therefore, this study proposes a structural displacement identification and quantification method that integrates YOLOv8n with an improved edge-orientation gradient-based template matching algorithm. By combining deep learning techniques with traditional template matching methods, the accuracy and robustness of monitoring are enhanced under adverse conditions such as noise and extremely low illumination. Specifically, in the edge-orientation gradient matching stage, the Canny-Devernay sub-pixel edge detection technique and an improved ellipse-fitting method are …

The George-Anne Daily, Georgia Southern University

George-Anne Media Group: Newsletters & Magazines

No abstract provided.

Markov-Modulated Queueing Network For Mobile Traffic Aggregation With Threshold-Controlled Buffers, Anton A. Esin, Elmira Yu. Kalimulina

Mathematical Modelling and Numerical Simulation with Applications

We study the problem of data transmission from mobile platforms operating in high-speed transit between cellular base stations, under conditions of unstable and intermittent connectivity. Conventional queueing and connectivity models often fail to capture the combined effects of rapidly changing signal conditions, finite buffer capacity, and dynamic topology. We aim to develop a tractable yet expressive model that integrates stochastic link availability, queue dynamics, and buffer control. We propose a mathematical framework based on queues whose service intensities are modulated by a continuous-time Markov chain (CTMC) representing signal conditions along a high-speed trajectory. The core subsystem is a two-stage (aggregation …

An Interpretable Hybrid Deep And Reinforcement Learning Paradigm For Glioma Prognosis, Renuga Devi M Ms

Theses and Dissertations

Brain tumors are highly aggressive and lethal types of cancer, particularly gliomas. These cancerous growths show complicated pathophysiological behaviours and with poor prognosis despite therapeutic advances. Due to their biological differences and infiltrating growth, as well as overlapping radiological characteristics, they pose great difficulty in diagnosis, grading, and survival prediction. Artificial intelligence technology, which includes machine learning , deep learning, and reinforcement learning has developed into a new paradigm for the automation of brain tumor diagnostics and personalized treatment. The main goal of this study is to create an integrated AI-based framework that can perform brain tumor segmentation, grading and …

Development Of Deep Fused Neural Architecture For Ancient Tamil Palm-Leaf Manuscript Recognition, Hariharan P Mr

Theses and Dissertations

Digitizing Tamil palm-leaf manuscripts is important for education, communication, and the preservation of cultural heritage. The complex structure of the Tamil script, the wide range of handwriting styles, and the degradation seen in ancient Tamil palm-leaf manuscripts make these texts very difficult to read and understand. Digital Image Processing (DIP), document analysis techniques, and traditional Optical Character Recognition (OCR) are unable to handle noise, background interference, faded ink, and limited labelled data, motivating the need for robust, effective Deep Learning (DL)- based solutions.

As a prerequisite to understanding and designing effective recognition systems for ancient manuscripts, this thesis first examines …

Axial Sulfur-Coordination Engineering Boosting Fe–N–C Catalysts For High-Performance Proton Exchange Membrane Fuel Cells, Lin Lin, Xiu-Xuan Hou, Zhe-Chen Fan, Yi-Xuan Yin, Wei-Yi Zhao, Kai Wei, Yu-Die Zhou, Li-Na Hou, Ying Wang, Hao Wan, Jun-Jie Ge

Journal of Electrochemistry

Fe-N-C catalysts have long suffered from kinetically sluggish oxygen reduction reaction (ORR) due to excessive adsorption strength toward oxygen intermediates and low site utilization. Heteroatom doping effectively accelerates ORR reaction kinetics through electronic structure modulation of metal sites for optimal intermediate adsorption, while chemical vapor deposition (CVD) enhances the turnover frequency (TOF) of active sites. Herein, we developed an FeSNC catalyst featuring abundant FeS₁N₄ sites via a dual-precursor CVD strategy. Experimental and theoretical analyses revealed that S incorporation disrupts the symmetric coordination of active sites, which optimizes OH* adsorption energies from 0.212 eV to 1.194 eV. Moreover, …

Entropy Of Metal/Solution Interfaces: Thermodynamic Framework, Theoretical Models, And Roles Of Interfacial Water, Zeng-Ming Zhang, Zi-Xi Liang, Jun Huang

Journal of Electrochemistry

Entropy is a basic thermodynamic property of the electrical double layer (EDL) at metal/solution interfaces, yet, its definition, measurement, and theoretical treatment are dispersed in the literature, and, in some cases, ambiguous. In this paper, we revisit the thermodynamic theory of EDL, from which two variants of entropy, excess entropy and formation entropy, are obtained and compared. In terms of the formation entropy, two calculation routes are validated in the context of a primitive EDL model, namely, the Gouy-Chapman (GC) model. After clarifying the concepts and calculation routes, we investigate interfacial water effects on the EDL entropy, using a refined …

Evaluating Runtime Monitoring For Reinforcement Learning-Based Flight Control, Andrew Zubyk

Doctoral Dissertations and Master's Theses

Ensuring safety in adaptive flight controls systems is an ongoing challenge in aviation, especially as advancements in artificial intelligence and machine learning (AI/ML) trend upwards. Reinforcement learning is becoming more common in aerospace applications due to the ability to improve these models through training.  While models such as reinforcement learning enable controllers to learn complex behaviors from interaction with the environment, their unpredictability in novel or disturbed conditions raises severe concerns in safety-critical domains. This research investigates the integration of runtime monitoring, a real-time assurance technique, with reinforcement learning-based flight controllers to ensure safety and reliability during flight. By supervising …

A Pretraining-Based Framework For On-Device Training Of Imu-Based Locomotion Mode Detection For Wearable Active Exoskeletons, Muhammad Tahir Khan

LSU Master's Theses

Active exoskeletons are being developed to support human movement in physically demanding industries such as construction. For these systems to work effectively, they must be able to correctly identify the user’s current activity. This process is known as locomotion mode detection and plays an important role in selecting the appropriate control parameters for exoskeletons. Many existing approaches use inertial measurement units (IMUs) to recognize these activities and have shown strong performance. However, most of these methods depend on large amounts of labeled data collected under specific conditions. As a result, they often do not perform well when applied to new …

Wearable Sensor System Used To Measure Linear And Angular Acceleration Of The Head Of American Football Players, David A. Emerson

LSU Master's Theses

American football players are repeatedly subject to high-velocity impacts; collisions can exceed 100 g in the NFL [1]. Rotational accelerations of the head caused by high-velocity collisions have been proven to be extremely damaging to the highly organized brain fibers at the brain-skull interface [2]. The sensor system (SS) measures the nonplanar acceleration at four locations on a chin strap using ADXL314 accelerometers and utilizes rigid-body kinematics to estimate the head rotational state from the measured acceleration of the SS [3]. The SS was validated through progressive testing, including steady-state, linear impact, and rotational impact testing. The ADLX314 sensor exhibited …

Sweep Angle Effects Of Flow Over A Seal Whisker-Inspired Undulated Cylinder, Trevor Dunt, Christin T. Murphy, Ondrej Fercak, Raúl Bayoán Cal, Jennifer A. Franck

Mechanical and Materials Engineering Faculty Publications and Presentations

Flow over a seal whisker-inspired undulated cylinder at swept back angles is computationally investigated, comparing the vortex shedding, forces, and wake characteristics to those of an equivalent smooth geometry. Numerous prior studies have demonstrated that undulated cylinders can reduce mean drag and unsteady lift oscillations; however, none have isolated the effects of the sweep angle resulting from whisker positioning in flow. Inspired by the active control seals exert over their whiskers while navigating and sensing in unsteady aquatic environments, this study investigates how such orientation influences the hydrodynamic performance of the geometry. Simulations are performed of flow across a rigid, …