Physical Sciences and Mathematics Commons^™

Unsupervised Dimension Reduction Techniques For Lung Diagnosis Using Radiomics, Janet Kireta

Electronic Theses and Dissertations

Over the years, cancer has increasingly become a global health problem [12]. For successful treatment, early detection and diagnosis is critical. Radiomics is the use of CT, PET, MRI or Ultrasound imaging as input data, extracting features from image-based data, and then using machine learning for quantitative analysis and disease prediction [23, 14, 19, 1]. Feature reduction is critical as most quantitative features can have unnecessary redundant characteristics. The objective of this research is to use machine learning techniques in reducing the number of dimensions, thereby rendering the data manageable. Radiomics steps include Imaging, segmentation, feature extraction, and analysis. For …

Predicting High-Cap Tech Stock Polarity: A Combined Approach Using Support Vector Machines And Bidirectional Encoders From Transformers, Ian L. Grisham

Electronic Theses and Dissertations

The abundance, accessibility, and scale of data have engendered an era where machine learning can quickly and accurately solve complex problems, identify complicated patterns, and uncover intricate trends. One research area where many have applied these techniques is the stock market. Yet, financial domains are influenced by many factors and are notoriously difficult to predict due to their volatile and multivariate behavior. However, the literature indicates that public sentiment data may exhibit significant predictive qualities and improve a model’s ability to predict intricate trends. In this study, momentum SVM classification accuracy was compared between datasets that did and did not …

Spin Trapping Behavior Of Some Selected Melatonin Derivatives For Hydroxyl Radicals: A Computational Study, Aaron Caesar

Electronic Theses and Dissertations

Melatonin (N-acetyl-5-methoxytryptamin, MLT) is a naturally occurring antioxidant which has shown some potential for use as a spin trap. Spin traps react with short lived hydroxyl radicals (HO·) to produce more stable products called spin adducts which may be characterized by electron paramagnetic resonance spectroscopy. However, the relative stability of hydroxyl spin adducts of melatonin derivatives (MLTD) compared to 2-hydroxymelatonin (HO-MLT) has not been examined computationally. Computational studies have been done on four selected MLTD; methylmelatonin (Me-MLT), chloromelatonin (Cl-MLT), cyanomelatonin (CN-MLT), and nitromelatonin (NO₂-MLT). Geometry of the structures were optimized at the HF/6-31G(d), cc-pVXZ, (X=D and T) and …

Assessing A Pandemic: Spatiotemporal Analysis Of Covid-19 In Tennessee School-Age Children, Omobolaji Olawuyi

Electronic Theses and Dissertations

This study is a spatiotemporal analysis of the COVID-19 pandemic in school-age children (5-18 years) in Tennessee, from 2020-03-19 to 2022-02-12. Trend Analysis, Emerging Hot Spot Analysis, and a time series revealed three significant waves in both age groups. Therefore, Change Point Detection at the county level was completed using six defined change points to identify the wax and wane of the three COVID-19 waves. Hierarchical Cluster Analysis grouped counties with similar change points into six clusters. No spatial pattern was observed in distribution of the six clusters, however, when each change point was evaluated separately, spatial autocorrelation was present, …

The Six Emotional Dimension (6de) Model: A Multidimensional Approach To Analyzing Human Emotions And Unlocking The Potential Of Emotionally Intelligent Artificial Intelligence (Ai) Via Large Language Models (Llm), Jay Ratican, James Hutson

Faculty Scholarship

The rapid advancements in artificial intelligence (AI) research, particularly in training large language models (LLMs) such as OpenAI's ChatGPT 3.5 and 4, hold significant potential for future applications in education, healthcare, and assisted living. Emotionally intelligent AI systems can provide personalized and adaptive educational experiences, enhancing engagement and educational outcomes. In healthcare, they can offer empathetic mental health support, augmenting existing resources. In assisted living, AI companions can provide emotional support, cognitive stimulation, and monitoring services, promoting independence and safety. However, ethical considerations and privacy safeguards are crucial to ensure responsible deployment. Integrating emotionally intelligent AI in these domains has …

Decision Support Issues In Automated Driving Systems, William N. Caballero, David Ríos Insua, David Banks

Faculty Publications

Machine learning and computational processing have advanced such that automated driving systems (ADSs) are no longer a distant reality. Many automobile manufacturers have developed prototypes; however, there exist numerous decision support issues requiring resolution to ensure mass ADS adoption. In the coming decades, it is likely that production ADSs will only be partially autonomous. Such ADSs operate within predetermined conditions and require driver intervention when they are violated. Since forecasts of their 20-year market penetration are relatively low, ADSs will likely operate in heterogeneous traffic characterized by vehicles of varying autonomy levels. Under these conditions, effective decision support must consider …

The Development Of Sociomathematical Norms In The Transition To Tertiary Exam-Oriented Individualistic Mathematics Education In An East Asian Context, Woong Lim, Hyunkyoung Yoon, Younggon Bae, Oh Nam Kwon

School of Mathematical & Statistical Sciences Faculty Publications

This study investigates social, mathematical, and sociomathematical norms perceived by college students in an engineering mathematics course and examines the students’ sense of mathematics as signals of individual merit. Data sources include a survey and one-on-one interviews with 38 students. The findings help illustrate student perceptions of academic social norms in a large-lecture course represented by the acquisition model of learning in college, detached from communal and collaborative disciplinary practices. Findings provide insights into the local educational context of an East Asian country as a case study when exam-oriented mathematics is institutionalized as normalcy.

The Safe And Effective Clinical Deployment Of Artificial Intelligence To Ols, Kelly Nealon

Dissertations and Theses (Open Access)

18 million new cancer cases are diagnosed each year. Roughly half of these patients will be treated with radiation therapy, a complex technique that requires an interdisciplinary team of clinical staff and expensive equipment to be delivered safely. Cancer centers in Low- and Middle-Income Countries (LMIC) have an especially difficult time meeting the demands of radiation therapy as the complexity of treatment techniques increase, with only 37% of patients in these regions having access to the care they need. Artificial Intelligence (AI) based tools are being developed to simplify the treatment planning and quality assurance processes to increase the number …

Relative Reactivity Of Six Amino Acids With Sodium Hypochlorite Measured By Gas Chromatography/ Mass Spectrometry And Methyl Chloroformate Derivatization., Josephine Wangui Gitau

Electronic Theses, Projects, and Dissertations

There are 20 common amino acids that act as building blocks for proteins and each one of them differ from each other due to their chemical structure of the R group. During the process of chlorination of water and wastewaters, amino acids present have been implicated as precursors of disinfection by-products. For the analysis of amino acids Gas Chromatography/Mass Spectrometry (GC/MS) is widely used. In this research six amino acids (glycine, valine, leucine, isoleucine, methionine, and phenylalanine) were derivatized with Methyl Chloroformate and analyzed using Gas Chromatography/Mass Spectrometry without heating. The main aim of this study was to observe the …

A Study Of Various Data Sizes Using Machine Learning, Sochaeta Koeum

Electronic Theses, Projects, and Dissertations

Social media is a great domain for news consumption; however, it is referred to as a double-edged sword. While it is user-friendly and low-cost, social media is the reason why fake news can spread rapidly, which is detrimental to society, businesses, and many consumers. Therefore, fake news detection is an emerging field. However, some challenges have restricted other researchers from developing a universal machine learning model that is fast, efficient, and reliable to stop the proliferation because of the lack of resources available, such as large-sized datasets. The goal of this culminating experience project is to explore how varying datasets …

Heart Disease Prediction Using Binary Classification, Virendra Sunil Devare

Electronic Theses, Projects, and Dissertations

In this project, I built a neural network model to predict heard disease with binary classification technique using patient information dataset from UCI Machine Learning repository. This dataset was preprocessed to remove missing elements and performed feature extraction. Our result shows that the model that I built has the best performance accuracy in heart disease classification if compared to other models and algorithms. The model achieved 94.98% accuracy after hyperparameter tuning and 0.947 area under the curve in ROC curve analysis. In addition, to identify the most important factors in heart disease prediction, I also performed feature importance analysis. Our …

The P-Adic Numbers And Conic Sections, Abdelhadi Zaoui

Electronic Theses and Dissertations

This thesis introduces the p-adic metric on the rational numbers. We then present the basic properties of this metric. Using this metric, we explore conic sections, viewed as equidistant sets. Lastly, we move on the sequences and series, and from there, we define p-adic expansions and the analytic completion of Q with respect to the p-adic metric, which leads to exploring some arithmetic properties of Qp.

Studying Developer Eye Movements To Measure Cognitive Workload And Visual Effort For Expertise Assessment, Salwa D. Aljehane, Bonita Sharif, Jonathan I. Maletic

School of Computing: Faculty Publications

Eye movement data provides valuable insights that help test hypotheses about a software developer’s comprehension process. The pupillary response is successfully used to assess mental processing effort and attentional focus. Relatively little is known about the impact of expertise level in cognitive effort during programming tasks. This paper presents a quantitative analysis that compares the eye movements of 207 experts and novices collected while solving program comprehension tasks. The goal is to examine changes of developers’ eye movement metrics in accordance with their expertise. The results indicate significant increase in pupil size with the novice group compared to the experts, …

Experimental Methodologies In Assessing Ceramic Shrinkage In Residual Fingerprints For Archaeological Application, Luke Aaron Burnor

Electronic Theses, Projects, and Dissertations

This research evaluates the extent of ceramic shrinkage using a natural clay source that was locally available and known to be used by native populations in the American Southwest. The experiment took into account variables of temper mixture and firing temperature to assess the extent and potential need for shrinkage calibration in archaeological biometric research (specifically fingerprints). An experimental design was employed to test shrinkage rates while accounting for natural temper materials found frequently in the archaeological record including sand, grog, and quartz. The experiment evaluated whether shrinkage rates may have skewed data collected in previous studies regarding sex and …

Soil Health And Remediation For Urban Gardens In Utah, Melissa Chilinski

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Urban environments are at an increased risk of soil contamination and poor soil health due to anthropogenic causes. As healthy farmland is developed, new urban farmers and gardeners are often left growing food on unwanted land with unknown histories of previous use. Varied research and methods for obtaining healthy soils can cause new growers to make decisions that negatively impact soil health and fertility, or on the other hand, conflicting information can cause individuals to become unnecessarily fearful of common soil contaminants and their effect on human health. Common soil contaminants, like trace metals (often referred to as heavy metals) …

Predictive Ecology And Management Of Phyllosphere Microbial Communities Through Cross-Scale Synthesis, David W. Armitage, Morgan E. Carter, Robin A. Choudhury, Mitja Remus-Emsermann, Cindy E. Morris, Johan H. Leveau, Linda L. Kinkel, José Pablo Dundore-Arias

School of Earth, Environmental, & Marine Sciences Faculty Publications

Here we summarize the main takeaways from a symposium and hybrid virtual and in-person participatory discussion focused on the challenges of scale in understanding the ecology and management of phyllosphere microbial communities. We provide an overview of the confounding effects of spatial scale on inference in microbial ecology, the spatial organization of microbial interactions in the phyllosphere, advances and remaining gaps in measuring phyllosphere colonization across scales, and the epidemiology in the phyllosphere. We hope to motivate further discussion and the development and adoption of creative approaches to solving the challenges of scale to enhance fundamental understanding and practical management …

Dual Crosslinked Poly(Acrylamide-Co-N-Vinylpyrrolidone) Microspheres With Re-Crosslinking Ability For Fossil Energy Recovery, Jingyang Pu, Baojun Bai, Jiaming Geng, Na Zhang, Thomas P. Schuman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Microspheres have been proposed to be applied in controlling wastewater production for mature oilfields and migrating leakage for gas and nuclear waste storage. However, it remains challenging for stacked microspheres to maintain strong blocking ability in micron-sized small pores or fractures. In this study, a novel microsphere was developed with comprehensive properties including high deformability and long re-crosslinking time upon tunable swelling ratio for the applications. A dual covalent and physical crosslinking strategy was used to develop novel microspheres reinforced by a hydrogen bond (H-bond, between pyrrole ring and amide group) and coordination bond (between chromium acetate (CrAc) and carboxyl …

Multiparametric Magnetic Resonance Imaging Artificial Intelligence Pipeline For Oropharyngeal Cancer Radiotherapy Treatment Guidance, Kareem Wahid

Dissertations and Theses (Open Access)

Oropharyngeal cancer (OPC) is a widespread disease and one of the few domestic cancers that is rising in incidence. Radiographic images are crucial for assessment of OPC and aid in radiotherapy (RT) treatment. However, RT planning with conventional imaging approaches requires operator-dependent tumor segmentation, which is the primary source of treatment error. Further, OPC expresses differential tumor/node mid-RT response (rapid response) rates, resulting in significant differences between planned and delivered RT dose. Finally, clinical outcomes for OPC patients can also be variable, which warrants the investigation of prognostic models. Multiparametric MRI (mpMRI) techniques that incorporate simultaneous anatomical and functional information …

Treatment Planning Automation For Rectal Cancer Radiotherapy, Kai Huang

Dissertations and Theses (Open Access)

Background

Rectal cancer is a common type of cancer. There is an acute health disparity across the globe where a significant population of the world lack adequate access to radiotherapy treatments which is a part of the standard of care for rectal cancers. Safe radiotherapy treatments require specialized planning expertise and are time-consuming and labor-intensive to produce.

Purpose:

To alleviate the health disparity and promote the safe and quality use of radiotherapy in treating rectal cancers, the entire treatment planning process needs to be automated. The purpose of this project is to develop automated solutions for the treatment planning process …

Deephtlv: A Deep Learning Framework For Detecting Human T-Lymphotrophic Virus 1 Integration Sites, Johnathan Jia, Johnathan Jia

Dissertations and Theses (Open Access)

In the 1980s, researchers found the first human oncogenic retrovirus called human T-lymphotrophic virus type 1 (HTLV-1). Since then, HTLV-1 has been identified as the causative agent behind several diseases such as adult T-cell leukemia/lymphoma (ATL) and a HTLV-1 associated myelopathy or tropical spastic paraparesis (HAM/TSP). As part of its normal replication cycle, the genome is converted into DNA and integrated into the genome. With several hundreds to thousands of unique viral integration sites (VISs) distributed with indeterminate preference throughout the genome, detection of HTLV-1 VISs is a challenging task. Experimental studies typically use molecular biology …

Bayesian Semi-Mechanistic Dose-Finding Designs For Phase I Oncology Trials, Chao Yang

Dissertations and Theses (Open Access)

Bayesian adaptive designs are getting more popular in research and in practice because they are flexible and efficient in evaluating an experimental drug. In oncology, despite the great advances in novel dose-finding designs, the high failure rates of clinical cancer drug development from phase I to III trials call for further improvements on novel designs, in addition to the need to promote and adopt novel designs in practice. Because anticancer agents often have a narrow therapeutic index, an accurate identification of the maximum tolerated dose (MTD) in a phase I trial is crucial for identifying a tolerable and efficacious dose …

Automating The Radiation Therapy Treatment Planning Process For Pediatric Patients With Medulloblastoma, Soleil Hernandez

Dissertations and Theses (Open Access)

Over the past 50 years, pediatric cancer 5-year survival rates increased from 20% to 80% in high-income countries, however, these trends have not been mirrored in low-and-middle-income countries (LMICs). This is due in part to delayed diagnosis, higher rates of advanced disease at presentation and a growing lack of access to high quality medical personnel and technology necessary to deliver complex treatments.

The long-term goal of this study was to alleviate demanding workflows and increase global access to high-quality pediatric radiation therapy by harnessing the power of artificial intelligence to automate the radiation therapy treatment planning process for pediatric patients …

Consumer Reaction To The Use Of Artificial Intelligence Chatbot On Distribution Of General Insurance In Singapore, Lai Hing Tan

Dissertations and Theses Collection (Open Access)

As technology rapidly permeates all aspects of our lives, it is not unusual to question and even challenge the rationale on why certain industries are slower to adapt to the new digital age. Insurance is a business that is under scrutiny given its traditional ways of selling and legacy challenges. Why is technology investment in insurance companies lagging others? One emerging technological disruption is artificial intelligence (AI). It is the science of designing and building intelligent systems that can complete tasks traditionally performed by humans. AI is expected to fundamentally transform today’s marketplace, for businesses and consumers alike. However, because …

Deep Learning-Based Turkish Spelling Error Detection With A Multi-Class False Positive Reduction Model, Burak Aytan, Cemal Okan Şakar

Turkish Journal of Electrical Engineering and Computer Sciences

Spell checking and correction is an important step in the text normalization process. These tasks are more challenging in agglutinative languages such as Turkish since many words can be derived from the root word by combining many suffixes. In this study, we propose a two-step deep learning-based model for misspelled word detection in the Turkish language. A false positive reduction model is integrated into the system to reduce the false positive predictions originating from the use of foreign words and abbreviations that are commonly used in Internet sharing platforms. For this purpose, we create a multi-class dataset by developing a …

A Case Study In Bivariate Spline Spaces, Ryann Lee Firestine

Graduate Theses and Dissertations (2019 - present)

Loosely speaking, splines are piece-wise polynomial functions which are continuously differentiable of order r. The individual polynomial segments are degree less than or equal to d. Splines are typically associated with approximation theory, computer-aided graphic design, and partial differential equations. Due to the wide variety of applications, mathematicians became interested in better understanding the behavior of the vector spaces containing splines in various setting and values r and d. In particular, many focused on formulating the dimension of these vector spaces. In the 1980s, commutative algebra was first applied to the study of spline spaces. In our work, we use …

A Framework For Identifying Malware Threat Distribution On The Dark Web, Shelby Caldwell

Graduate Theses and Dissertations (2019 - present)

The Dark Web is an ever-growing phenomenon that has not been deeply explored. It is no secret that in recent years, malware has become a powerful threat to technology users. The Dark Web is known for supporting anonymity and secure connections for private interactions. Over the years, it has become a rich environment for displaying trends, details, and indicators of emerging malware threats. Through the application of data science and open-source intelligence techniques, trends in malware distribution can be studied. In this research, we create a framework for helping identify malware threat distribution patterns. We examine this type of Dark …

Risk Assessment Framework For Evaluation Of Cybersecurity Threats And Vulnerabilities In Medical Devices, Maureen S. Van Devender

Graduate Theses and Dissertations (2019 - present)

Medical devices are vulnerable to cybersecurity exploitation and, while they can provide improvements to clinical care, they can put healthcare organizations and their patients at risk of adverse impacts. Evidence has shown that the proliferation of devices on medical networks present cybersecurity challenges for healthcare organizations due to their lack of built-in cybersecurity controls and the inability for organizations to implement security controls on them. The negative impacts of cybersecurity exploitation in healthcare can include the loss of patient confidentiality, risk to patient safety, negative financial consequences for the organization, and loss of business reputation. Assessing the risk of vulnerabilities …

Determination Of Cadmium Uptake In Crassostrea Virginica Shell Under Controlled Conditions, Joseph John Pavelites Ii

Graduate Theses and Dissertations (2019 - present)

The objective of this thesis was to meet growing demand for the development of environmental biomonitors that protect ecosystems and public health. To do this, I determined the potential of oyster shell as a bioindicator of cadmium (Cd) in the environment by determining the mode of Cd uptake and relationships between Cd concentrations in the environment, shell, and soft tissues of juvenile eastern oysters (Crassostrea virginica Gmelin). I performed a review of the literature on the ability of oyster shell to retain metal contaminants and the factors that could affect this process (Chapter 2). I then reared C. virginica …

A Study Of Gold Nanoparticles Of Different Sizes With Raman Labels For Surface Enhanced Raman Spectroscopic Detection, Melissa M. Hader

Undergraduate Honors Theses

According to the Center for Disease Control and Prevention, the second leading cause of death in the United States is cancer, with 602,350 cancer deaths in 2020. With the current cancer detection techniques, the detection of cancer is often at a stage when the cancer has progressed to dangerous levels. Therefore, being able to detect cancer at its early stages is pivotal and can be life altering for millions. Gold nanoparticles (AuNPs) have been widely explored in developing surface-enhanced Raman scattering (SERS) techniques for early detection of cancer biomarkers. Using gold nanoparticles conjugated with Raman reporter molecules, SERS is a …

Synthesis And Characterization Of Nanocomposite Sensing Films For Breath Sensors, Tara Mercer

Undergraduate Honors Theses

Lung cancer is one of the most common and fatal cancers today, infecting 1 in 16 people, and killing well over a million patients per year. Currently, lung cancer is detected usually in stages three and four by quite costly and invasive methods, which shows only a survival rate of 10%. Breath sensors provide a low-cost and non-invasive technique for early screening of lung cancer. The breath sensors use assemblies of gold nanoparticles to identify lung cancer, specifically by identifying and quantifying specific volatile organic compound (VOC) concentrations found in the breath of lung cancer patients. This thesis describes a …