Digital Commons Network^™

Machine Learning-Based Gps Jamming And Spoofing Detection, Alberto Squatrito

Doctoral Dissertations and Master's Theses

The increasing reliance on Global Positioning System (GPS) technology across various sectors has exposed vulnerabilities to malicious attacks, particularly GPS jamming and spoofing. This thesis presents an analysis into detection and mitigation strategies for enhancing the resilience of GPS receivers against jamming and spoofing attacks. The research entails the development of a simulated GPS signal and a receiver model to accurately decode and extract information from simulated GPS signals. The study implements the generation of jammed and spoofed signals to emulate potential threats faced by GPS receivers in practical settings. The core innovation lies in the integration of machine learning …

The Advancement Of Experimental And Computation Tools For The Study Of Molten Salt Chemistry To Facilitate The Extraction Of Strategic Elements In Nuclear Applications, Michael Stoddard

Theses and Dissertations

Nuclear energy presents environmental benefits, yet the challenge of radioactive waste management persists. Advanced solutions, such as Molten Salt Reactors (MSRs), require a more profound understanding of molten salt chemistry. This research aims to develop tools, including a depletion simulator, molten salt electrochemical simulator, and a fluoride-based thermodynamic reference electrode for electrochemical purification. The computationally inexpensive depletion simulator allows for exploration into extraction and processing strategies for molten salt reactors. An illustrative case study on Mo-99 production from MSRs demonstrates the practical application of the theoretical framework, emphasizing the need for optimization in extraction effectiveness and separation difficulty. The electrochemical …

Secured Blockchain And Fractional Discrete Cosine Transform-Based Framework For Medical Images, Abhay Kumar Yadav, Virendra P. Vishwakarma

Makara Journal of Technology

Images can store large amounts of data and are useful for transmitting large amounts of information across different geographical locations using different cloud services. This data sharing increases the chances of cyber-attacks on digital images. Blockchain has properties that enable it to work as a solution to this problem, providing enhanced security and unchangeable storage. However, image size poses a challenge in image storage, as it increases the related storage cost. Compressing images using fractional discrete cosine transform (fctDCT) reduces the amount of data required to express an image securely. This paper presents a novel framework for securely storing and …

Sulphate Contamination In An Abandoned Coal Mine In Light Of Mining Effects, Qi Yueming, Zhou Pei, Zhou Lai, Jiang Dan, Yang Yuqing, Liu Yanzhuo

Coal Geology & Exploration

Abandoned high-sulfur coal mines will become deeply buried acid-producing contamination sites, posing hazards to adjacent aquifers and surrounding environments. Furthermore, mining effects and the complex spatial distribution of abandoned mines complicate the assessment of the contamination processes and degrees in adjacent aquifers. Focusing on a certain abandoned coal mine, this study examined the migration characteristics of SO₄ ²⁻ pollution in acid mine drainage using numerical simulations by taking sulfate (SO₄ ²⁻) as the characteristic contaminant and considering the effects of the fractures formed by the mining of multiple coal seams on the aquifer structure. Furthermore, it analyzed …

Comparison Of Four In Vitro Test Methods To Assess Nucleus Pulposus Replacement Device Expulsion Risk, Tahmanna Rahman, Matthew J. Kibble, Gianluca Harbert, Nigel Smith, Erik Brewer, Thomas P. Schaer, Nicolas Newell

Rowan-Virtua School of Translational Biomedical Engineering & Sciences Departmental Research

Background

Nucleus replacement devices (NRDs) are not routinely used in clinic, predominantly due to the risk of device expulsion. Rigorous in vitro testing may enable failure mechanisms to be identified prior to clinical trials; however, current testing standards do not specify a particular expulsion test. Multiple methods have therefore been developed, complicating comparisons between NRD designs. Thus, this study assessed the effectiveness of four previously reported expulsion testing protocols; hula-hoop (Protocol 1), adapted hula-hoop (Protocol 2), eccentric cycling (Protocol 3), and ramp to failure (Protocol 4), applied to two NRDs, one preformed and one in situ curing.

Methods

Nucleus material …

Comparison Of Four In Vitro Test Methods To Assess Nucleus Pulposus Replacement Device Expulsion Risk, Tamanna Rahman, Matthew J. Kibble, Gianluca Harbert, Nigel Smith, Erik Brewer, Nicholas Newell

Rowan-Virtua School of Translational Biomedical Engineering & Sciences Departmental Research

Background: Nucleus replacement devices (NRDs) are not routinely used in clinic, predominantly due to the risk of device expulsion. Rigorous in vitro testing may enable failure mechanisms to be identified prior to clinical trials; however, current testing standards do not specify a particular expulsion test. Multiple methods have therefore been developed, complicating comparisons between NRD designs. Thus, this study assessed the effectiveness of four previously reported expulsion testing protocols; hula-hoop (Protocol 1), adapted hula-hoop (Protocol 2), eccentric cycling (Protocol 3), and ramp to failure (Protocol 4), applied to two NRDs, one preformed and one in situ curing. Methods: Nucleus material …

Mineral Matter Behavior During The Combustion Of Biomass And Coal Blends And Its Effect On Particulate Matter Emission, Ash Deposition, And Sulfur Dioxide Emission, Rajarshi Roy

Theses and Dissertations

Combustion of coal is one of the primary sources of electricity generation worldwide today. Coal contains different chemicals that cause particulate matter(PM) and sulfur dioxide (SO2) emissions. These are health hazards and are responsible for deteriorating the ambient air quality. Particulate matter also forms ash deposits inside the coal combustor, which in turn decreases the energy efficiency of the power plants. Using biomass as a fuel in these utility boilers can potentially reduce the problems of particulate matter emissions and ash deposition, and can significantly reduce the SO2 emissions. However, biomass needs to be pretreated to make its properties similar …

Stress And Exercise In Part 141 Flight Students, Reece Curcio, Thomas Vincent Hayes, Reon Porter, Brooke Wheeler

Aeronautics Student Publications

This study explores how stress levels relate to exercise habits among aviation students in a Part 141 collegiate flight program. There was no correlation between stress and exercise. This outcome was unexpected as the hypothesis was an inverse relationship between perceived stress and exercise.

Sparse Ensemble Networks For Hypserspectral Image Classification, Rakesh Kumar Iyer, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

We explore the efficacy of sparsity and ensemble model in the classification of hyperspectral images, a pivotal task in remote sensing applications. While Convolutional Neural Networks (CNNs) and Transformer models have shown promise in this domain, each exhibits distinct limitations; CNNs excel in capturing the spatial/local features but falter to capture spectral features, whereas Transformers captures the spectral features at the expense of spatial features. Furthermore, the computational cost associated with training several independent CNN and Transformer networks becomes expensive. To address these limitations, we propose a novel ensemble framework comprising pruned CNNs and Transformers, optimizing both spatial and spectral …

Mathematical Modeling For Dental Decay Prevention In Children And Adolescents, Mahdiyeh Soltaninejad

Dissertations

The high prevalence of dental caries among children and adolescents, especially those from lower socio-economic backgrounds, is a significant nationwide health concern. Early prevention, such as dental sealants and fluoride varnish (FV), is essential, but access to this care remains limited and disparate. In this research, a national dataset is utilized to assess sealants' reach and effectiveness in preventing tooth decay, particularly focusing on 2nd molars that emerge during early adolescence, a current gap in the knowledge base. FV is recommended to be delivered during medical well-child visits to children who are not seeing a dentist. Challenges and facilitators in …

Microgravity Aeroponics System Project, Andrew W. Diddle

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Science and Engineering at Morehead State University in partial fulfillment of the requirements for the degree Master of Science by Andrew W. Diddle on April 22, 2024.

Predicting Hospitalization Risk Of Schizophrenia Patients In Missouri, Arun Kumar

Theses

Understanding the factors that contribute to the risk of hospitalization among individuals with schizophrenia is crucial for optimizing treatment strategies and improving patient outcomes. In this study, we used recent Medicaid adminis trative claims data in Missouri (from 2016 to 2019) and predicted the risk of hospitalization of patients diagnosed with Schizophrenia (N=143446). We ana lyzed the association between previous hospitalizations and the likelihood of future hospitalizations. We developed machine learning techniques, including logistic re gression and decision tree classifiers, to predict the risk of hospitalization based on demographic factors, clinical variables, and historical hospitalization records. Our findings reveal that …

Phosphorus Soprtion Experiments: Impacts On Water Column Phosphate Concentrations In Utah Lake, Rebecca Layne Butters

Theses and Dissertations

Utah Lake, located in north-central Utah, USA, is a freshwater lake with a large surface area, shallow depth, and phosphorus-rich sediment with significant water-sediment interaction. These factors cause unique phosphorus behavior relative to other lake ecosystems, governed by sediment-water interactions. We hypothesize that benthic sediments and suspended solids act, by sorption processes, to maintain water column P concentrations that are largely insensitive to P inflows. We conducted a Phosphorus Addition Experiment to characterize sorbed P fluxes in the lake. Our experimental procedure included bench-scale laboratory experiments testing Utah Lake water and sediment with dilute and augmented P levels, as well …

Development Of A Molten Salt Reactor Design And Design Framework For Overall Reactor Performance Prediction And Optimization, Andrew William Larsen

Theses and Dissertations

This dissertation introduces a novel approach to nuclear reactor design, emphasizing molten salt reactors (MSRs) to address the global need for safer, more efficient, and sustainable energy sources. It confronts the inherent challenges of nuclear fission reactors--proliferation risks, cost efficiency, waste management, and passive accident prevention--by developing an innovative MSR model and a machine learning (ML)-based optimization framework. The molten salt microreactor (MSMR), devised by researchers at Brigham Young University, utilizes thermally conductive plates for efficient heat dissipation during operational anomalies, ensuring safety within operational limits. This design was rigorously tested using STARCCM+ for fluid dynamics modeling and RELAP5-3D for …

Emerging Technologies For Automation In Environmental Sensing: Review, Shekhar Suman Borah, Aaditya Khanal, Prabha Sundaravadivel

Electrical Engineering Faculty Publications and Presentations

This article explores the impact of automation on environmental sensing, focusing on advanced technologies that revolutionize data collection analysis and monitoring. The International Union of Pure and Applied Chemistry (IUPAC) defines automation as integrating hardware and software components into modern analytical systems. Advancements in electronics, computer science, and robotics drive the evolution of automated sensing systems, overcoming traditional limitations in manual data collection. Environmental sensor networks (ESNs) address challenges in weather constraints and cost considerations, providing high-quality time-series data, although issues in interoperability, calibration, communication, and longevity persist. Unmanned Aerial Systems (UASs), particularly unmanned aerial vehicles (UAVs), play an important …

Low Impedance, Durable, Self-Adhesive Hydrogel Epidermal Electrodes For Electrophysiology Recording, Naiyan Wu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Traditional electrodes used for electrophysiology recording, characterized by their hard, dry, and inanimate nature, are fundamentally mismatched with the soft, moist, and bioactive characteristics of biological tissues, leading to suboptimal skin-electrode interfaces. Hydrogel materials, mirroring the high water content and biocompatibility of biological tissues, emerge as promising candidates for epidermal electronic materials due to their adjustable physicochemical properties. However, challenges such as inadequate electrical conductivity, elevated skin impedance, unreliable adhesion in moist conditions, and performance decline from dehydration have significantly restricted the efficacy and applicability of hydrogel-based electrodes. In this thesis, we report a high-performance hydrogel epidermal electrode patch for …

Faa Medical Reform, Dana Rose

Honors Projects

This project investigates the challenges and implications of obtaining medical certification for pilots with a history of childhood misdiagnoses, focusing on Attention-Deficit/Hyperactivity Disorder (ADHD). Misdiagnoses in childhood can lead to significant obstacles in the aviation industry's medical certification process, posing unique hurdles for aspiring pilots. The study examines the current FAA guidelines and procedures for medical certification, particularly the evaluation requirements for individuals with ADHD. It also explores common challenges faced by pilots, the effects of childhood misdiagnoses on their eligibility, and the impact of the FAA's ADHD evaluation process.

Through interviews with Aviation Medical Examiners (AMEs), this project identifies …

Assessing The Need For A Mental Health Task Force For Aviation Science Students At Bridgewater State University, Cooper Castellone

Honors Program Theses and Projects

In the current landscape of aviation, the issue of mental health is of great concern, particularly among flight training students who have shown to grapple with depression in silence. A report issued by the Pilot Mental Health Aviation Rulemaking Committee in April 2024 underscored seven significant barriers impeding pilots from seeking necessary support for mental health concerns. Consequently, we completed a study aimed at understanding the prevailing mental health challenges among flight training students and identify strategies for institutions such as Bridgewater State University (BSU) to offer meaningful assistance. Our study consisted of a survey distributed to 14 institutions in …

A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka

Cybersecurity Undergraduate Research Showcase

The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …

Breast Cancer Classification With Machine Learning, Rahanuma Tarannum

ATU Scholars Symposium

Breast cancer is one of the foremost causes of death amongst women worldwide. Breast tumours are characteristically classified as either benign (non-cancerous) or malignant (cancerous). Benign tumours do not spread external side of the breast and are not fatal, whereas malignant tumours can metastasize and be incurable if untreated. Rapidly and accurate diagnosis of malignant tumours is significant for efficient treatment and advanced outcomes. In 2022, breast cancer claimed 670 000 lives worldwide. Women without any particular risk factors other than age and sex account for half of all cases of breast cancer. In 157 out of 185 nations, breast …

Ambulatory Electrocardiographic Monitoring, Genesis V. Garay, Arath Sanchez

ATU Scholars Symposium

•Cardiovascular disease (CVD) is the world's leading cause of death, especially prevalent in low- and middle-income countries. Up to 80% of premature heart attacks and strokes are preventable. •Current ambulatory electrocardiographic (ECG) monitors, while effective in diagnosing heart rhythm issues, are often cost-prohibitive and have limitations like short monitoring periods, user-initiated recording, and offline data analysis. •This poster summarizes the foundation of the creation of a monitoring system that attempts to address these issues.

Environmental Health Impacts Of Small-Scale Gold Mining In East Indonesia: Mercury Pollution And Nature Conservation, Tri Edhi Budhi Soesilo, Nada Ismita Hawa, Nuraeni Nuraeni

Journal of Sustainable Mining

The expansion of small-scale gold mining impacts environmental health and socioeconomic. Research in Bombana District, one of the gold mining centers in eastern Indonesia, was conducted to explore perceptions of the impact of small-scale gold mining on human health and attitudes towards environmental conservation activities related to small-scale gold mining activities. This research uses a quantitative approach with univariate tests to identify respondent characteristics, bivariate tests (Chi-square) to test relationships and frequency differences, and multivariate analysis (regression) to test the direction and magnitude of the relationship. The perception of the impact of small-scale gold mining on human health was not …

Enhancing Disease Detection In South Asian Freshwater Fish Aquaculture Through Convolutional Neural Networks, Hayin Tamut, Musfikur Rahaman, Dr. Robin Ghosh

ATU Scholars Symposium

Aquaculture expansion necessitates innovative disease detection methods for sustainable production. This study investigates the efficacy of Convolutional Neural Networks (CNNs) in classifying diseases affecting South Asian freshwater fish species. The dataset comprises 1747 images representing 7 class, healthy specimens and various diseases: bacterial, fungal, parasitic, and viral. The CNN architecture includes convolutional layers for feature extraction, max-pooling layers for down sampling, dense layers for classification, and dropout layers for regularization. Training employs categorical cross-entropy loss and the Adam optimizer over 30 epochs, monitoring both training and validation performance. Results indicate promising accuracy levels, with the model achieving 92.14% and test …

Mechanical Characterization Of Hemp, Jute, And Flax Based Natural Fibre Composites For Non-Structural Applications In Aircraft And Automobiles, Ravi Kumar B

Theses and Dissertations

Demand for reducing energy consumption and detrimental environmental impacts after the effective lifetime of an engineering material are the major driving factors for the development of natural fibre reinforced composites (NFRCs) in various sectors. Compared to synthetic fibre like carbon-fibres or Kevlar, natural fibres provide several benefits including light weight, inexpensive, recyclability, superior specific strength, biodegradable, non-toxic during handling, and less energy intensive during manufacturing. This doctoral work presents observations from mechanical tests and interpretations on the suitability of natural fibre reinforced composites for less heavily loaded engineering applications areas.

In the first stage, jute, flax, and hemp fibres were …

Advancing Brain Tumor Segmentation With Spectral–Spatial Graph Neural Networks, Sina Mohammadi, Mohamed Allali

Engineering Faculty Articles and Research

In the field of brain tumor segmentation, accurately capturing the complexities of tumor sub-regions poses significant challenges. Traditional segmentation methods usually fail to accurately segment tumor subregions. This research introduces a novel solution employing Graph Neural Networks (GNNs), enriched with spectral and spatial insight. In the supervoxel creation phase, we explored methods like VCCS, SLIC, Watershed, Meanshift, and Felzenszwalb–Huttenlocher, evaluating their performance based on homogeneity, moment of inertia, and uniformity in shape and size. After creating supervoxels, we represented 3D MRI images as a graph structure. In this study, we combined Spatial and Spectral GNNs to capture both local and …

Acoustothermal Transfection For Cell Therapy, Xiufang Liu, Ning Rong, Zhenhua Tian, Joseph Rich, Lili Niu, Pengqi Li, Laixin Huang, Yandai Dong, Wei Zhou, Pengfei Zhang, Yizhao Chen, Congzhi Wang, Long Meng, Tony Jun Huang, Hairong Zheng

Faculty Publications

Transfected stem cells and T cells are promising in personalized cell therapy and immunotherapy against various diseases. However, existing transfection techniques face a fundamental trade-off between transfection efficiency and cell viability; achieving both simultaneously remains a substantial challenge. This study presents an acoustothermal transfection method that leverages acoustic and thermal effects on cells to enhance the permeability of both the cell membrane and nuclear envelope to achieve safe, efficient, and high-throughput transfection of primary T cells and stem cells. With this method, two types of plasmids were simultaneously delivered into the nuclei of mesenchymal stem cells (MSCs) with efficiencies of …

Development Of An E-Governance Solution For Process Safety Management (Psm) Compliance, Dheerajkumar R Narang

Harrisburg University Experiential Learning Projects

E-governance (digital solutions) is the new norm in delivering numerous government services from government to citizens, businesses, institutions, and even other governments across all industry segments. One important application of digital solutions, in the governance space, can potentially be to comprehensively audit and intermittently monitor compliance of process plants with the regional process safety management (PSM) regulations. This presentation unveils the idea of an e-governance PSM solution that will potentially enable the relevant regulatory bodies around the world to seamlessly monitor and intermittently audit the process safety management (PSM) compliance through a digital solution. The presentation builds on an earlier …

Modeling The Human Learning Process Using An Industrial Steam Boiler Analogy To Design A Psychophysiological-Based Hypermedia Adaptive Automation System, Liliana María Villavicencio López

USF Tampa Graduate Theses and Dissertations

This dissertation aims to address the existing gap in the integration of various dimensions within the student learning system, encompassing cognitive, emotional, and physical variables. The primary objective is to construct a Personalized Learning Adaptive Automation model using Electroencephalography (EEG) technology.

To provide deeper insight into the intricate nature of the Human Learning Process, this study introduces a novel analogy with an Industrial Steam Boiler. This analogy serves as a distinctive contribution to research in the field.

The research methodology involved the collection of brainwaves data from engineering students while they undertook educational tasks of varying levels of difficulty, categorized …

Wireless Insights Into Cognitive Wellness: A Paradigm Shift In Alzheimer’S Detection Through Ultrathin Wearable Antennas, Fatma Taher, Moath Alathbah, M. Abdel-Aleim M., Thamer Alghamdi, Mohamed Fathy Abo Sree, Sara Yehia Abdel Fatah

All Works

The Proposed algorithm, designed to simulate an Alzheimer’s disease (AD) brain model across different stages, presents an invaluable opportunity for further research and in-depth study of the effects of AD. Currently, there is a notable absence of a comprehensive simulated model for the AD brain that allows the exploration of all AD biomarkers within a simulation tool. This represents a crucial advancement in the field, enabling researchers to thoroughly investigate and understand the diverse biomarkers associated with AD without resorting to highly expensive and ionizing radiation techniques. The algorithm’s capability to emulate various stages of AD in a simulated environment …

Energy-Absorbing Helmet For Safer Football, Aidan Laudeman

Honors Theses

Football-related injuries are a common occurrence and are often detrimental to the player’s health. Force impacts frequently occur at the front, back, and sides of a player’s helmet, resulting in head injuries like concussions. The goal of this project is to reduce recurrent head injuries by designing a solution involving the use of energy-absorbing metallic materials that are inserted into a football helmet. These energy-absorbing materials are configured in target zones inside the helmet to reduce the acceleration of the head based on impact locations. The chosen materials are nitinol and spring steel, which display energy-absorbing properties. Various energy-absorbing material …