Data Science Commons^™

Examining The Impact Of Customer Rfp Characteristics On Award Compliance, Laasya Ravipati

Data Science Undergraduate Honors Theses

In the context of intermodal transportation, understanding the dynamics of award compliance holds significant importance for operational efficiency and strategic decision-making. Award compliance refers to the percentage of awarded freight volume that is realized, indicating the extent to which contractual agreements are fulfilled. This analysis delves into the intricate relationship between customer characteristics and award compliance, aiming to provide valuable insights into the variability and predictability of compliance rates. By analyzing Request for Pricing (RFP) data and primary awarded freight volumes, the study seeks to address the need for more accurate volume estimations, crucial for sales planning, revenue projections, and …

Examining Award Compliance To Inform Resource Allocation, Jacob Haarala

Data Science Undergraduate Honors Theses

This project focuses on JB Hunt Transport Inc's intermodal business unit (JBI) by focusing on the challenges associated with Published Pricing and Contractual Pricing. The primary issue revolves around the variance between the awarded freight volumes in Requests for Pricing (RFPs) and the actual volumes realized when the freight is shipped. This discrepancy poses challenges for effective sales planning, revenue goals, and optimal freight network management within JBI. Reporting tools, such as PowerBI, are currently used by JBI to provide insights into award compliance on a weekly basis. However, our goal with this project was to provide a deeper understanding …

The Effects Of Using Machine Translators On The Performance Of Second Language Learners, Kasey Myer

University Honors College

With the rise of technology has also come the development of various online language translators and artificial intelligence that are often utilized by individuals learning a second language. However, there is a wide range of quality between the different machine translation tools, and many people tend to be under the impression that it is inferior to the quality of interpretations provided by human translators. This paper considers the positives and negatives of machine translation as a tool for second language learning. Variations between the input and output languages on a grammatical and cultural level are analyzed. Machine translation is compared …

Per- And Polyfluoroalkyl Substance Exposure Risks In Us Carceral Facilities, 2022, Lindsay Poirier, Derrick Salvatore, Phil Brown, Alissa Cordner, Kira Mok, Nicholas Shapiro

Statistical and Data Sciences: Faculty Publications

Objectives. To assess the US incarcerated population’s risk of exposure to per- and polyfluoroalkyl substances (PFASs). Methods. We assessed how many of the 6118 US carceral facilities were located in the same hydrologic unit code watershed boundaries as known or likely locations of PFAS contamination. We conducted geospatial analyses on data aggregated from Environmental Protection Agency databases and a PFAS site tracker in 2022 to model the hydrologically feasible known and presumptive PFAS contamination sites for nearly 2 million incarcerated people. Results. Findings indicate that 5% (∼310) of US carceral facilities have at least 1 known source of PFAS contamination …

Age At Lung Cancer Diagnosis In Females Versus Males Who Never Smoke By Race And Ethnicity, Batel Blechter, Jason Y Y Wong, Li-Hsin Chien, Kouya Shiraishi, Xiao-Ou Shu, Qiuyin Cai, Wei Zheng, Bu-Tian Ji, Wei Hu, Mohammad L Rahman, Hsin-Fang Jiang, Fang-Yu Tsai, Wen-Yi Huang, Yu-Tang Gao, Xijing Han, Mark D Steinwandel, Gong Yang, Yihe G Daida, Su-Ying Liang, Scarlett L Gomez, Mindy C Derouen, W Ryan Diver, Ananya G Reddy, Alpa V Patel, Loïc Le Marchand, Christopher Haiman, Takashi Kohno, Iona Cheng, I-Shou Chang, Chao Agnes Hsiung, Nathaniel Rothman, Qing Lan

Faculty, Staff and Student Publications

BACKGROUND: We characterized age at diagnosis and estimated sex differences for lung cancer and its histological subtypes among individuals who never smoke.

METHODS: We analyzed the distribution of age at lung cancer diagnosis in 33,793 individuals across 8 cohort studies and two national registries from East Asia, the United States (US) and the United Kingdom (UK). Student's t-tests were used to assess the study population differences (Δ years) in age at diagnosis comparing females and males who never smoke across subgroups defined by race/ethnicity, geographic location, and histological subtypes.

RESULTS: We found that among Chinese individuals diagnosed with lung cancer …

Natural Language Processing Of Clinical Notes Enables Early Inborn Error Of Immunity Risk Ascertainment, Kirk Roberts, Aaron T Chin, Klaus Loewy, Lisa Pompeii, Harold Shin, Nicholas L Rider

Faculty, Staff and Student Publications

BACKGROUND: There are now approximately 450 discrete inborn errors of immunity (IEI) described; however, diagnostic rates remain suboptimal. Use of structured health record data has proven useful for patient detection but may be augmented by natural language processing (NLP). Here we present a machine learning model that can distinguish patients from controls significantly in advance of ultimate diagnosis date.

OBJECTIVE: We sought to create an NLP machine learning algorithm that could identify IEI patients early during the disease course and shorten the diagnostic odyssey.

METHODS: Our approach involved extracting a large corpus of IEI patient clinical-note text from a major …

Improvements In Appropriate Placement Of Dental Sealants After Implementation Of A Clinical Decision Support System, Joanna Mullins, Ryan Brandon, Nicholas Skourtes, Elsbeth Kalenderian, Muhammad Walji

Faculty, Staff and Student Publications

BACKGROUND: Dental sealants are effective for the prevention of caries in children at elevated risk levels, and increasing the proportion of children and adolescents who have dental sealants on 1 or more molars is a Healthy People 2030 objective. Electronic health record (EHR)-based clinical decision support systems (CDSSs) have the ability to improve patient care. A dental quality measure related to dental sealant placement for children at elevated risk of caries was targeted for improvement using a CDSS.

METHODS: A validated dental quality measure was adapted to assess a patient's need for dental sealant placement. A CDSS was implemented to …

Bacteria Synergized With Pd-1 Blockade Enhance Positive Feedback Loop Of Cancer Cells-M1 Macrophages-T Cells In Glioma, Qi Chen, Yuyi Zheng, Xiaojie Chen, Yuan Xing, Jiajie Zhang, Xinyi Yan, Qi Zhang, Di Wu, Zhong Chen

Faculty, Staff and Student Publications

Cancer immunotherapy is an attractive strategy because it stimulates immune cells to target malignant cells by regulating the intrinsic activity of the immune system. However, due to lacking many immunologic markers, it remains difficult to treat glioma, a representative "cold" tumor. Herein, to wake the "hot" tumor immunity of glioma, Porphyromonas gingivalis (Pg) is customized with a coating to create an immunogenic tumor microenvironment and further prove the effect in combination with the immune checkpoint agent anti-PD-1, exhibiting elevated therapeutic efficacy. This is accomplished not by enhancing the delivery of PD-1 blockade to enhance the effect of immunotherapy, but by …

Leveraging Logical Definitions And Lexical Features To Detect Missing Is-A Relations In Biomedical Terminologies, Rashmie Abeysinghe, Fengbo Zheng, Jay Shi, Samden D Lhatoo, Licong Cui

Faculty, Staff and Student Publications

Biomedical terminologies play a vital role in managing biomedical data. Missing IS-A relations in a biomedical terminology could be detrimental to its downstream usages. In this paper, we investigate an approach combining logical definitions and lexical features to discover missing IS-A relations in two biomedical terminologies: SNOMED CT and the National Cancer Institute (NCI) thesaurus. The method is applied to unrelated concept-pairs within non-lattice subgraphs: graph fragments within a terminology likely to contain various inconsistencies. Our approach first compares whether the logical definition of a concept is more general than that of the other concept. Then, we check whether the …

Montelukast As A Repurposable Additive Drug For Standard-Efficacy Multiple Sclerosis Treatment: Emulating Clinical Trials With Retrospective Administrative Health Claims Data, Astrid M Manuel, Assaf Gottlieb, Leorah Freeman, Zhongming Zhao

Faculty, Staff and Student Publications

BACKGROUND: Effective and safe treatment options for multiple sclerosis (MS) are still needed. Montelukast, a leukotriene receptor antagonist (LTRA) currently indicated for asthma or allergic rhinitis, may provide an additional therapeutic approach.

OBJECTIVE: The study aimed to evaluate the effects of montelukast on the relapses of people with MS (pwMS).

METHODS: In this retrospective case-control study, two independent longitudinal claims datasets were used to emulate randomized clinical trials (RCTs). We identified pwMS aged 18-65 years, on MS disease-modifying therapies concomitantly, in de-identified claims from Optum's Clinformatics

RESULTS: pwMS treated with montelukast demonstrated a statistically significant 23.6% reduction in relapses compared …

Plumbing The Depths Of The Shallow End: Exploring Persistent Homology Using Small Data, R. Anne Flynn

All NMU Master's Theses

Persistent homology is a prominent tool in topological data analysis. This thesis is designed to be an introduction and guide to a beginner in persistent homology. This comprehensive overview discusses the math used behind it, the code needed to apply it, and its current place in the field. We explain and demonstrate the algebraic topology which fuels persistent homology. Homotopies inspire homology groups, which are able to determine how many holes a shape has. By visualizing data as a shape, persistent homology determines what type of holes are present.

We demonstrate this by using the package TDA in the manipulation …

Analyzing Information Diffusion In Social Media Networks, Amin Riazi

Masters Theses and Doctoral Dissertations

Social media is a dynamic platform where a wide range of information is shared, including both true and false content, and it involves interactions between human users and social bots. This study investigates information diffusion patterns on X (formerly Twitter) by analyzing retweet (repost) network topologies. The results reveal distinct behavioral patterns for humans and bots when spreading true and false information, highlighting the need for further examination of their roles in information dissemination. Moreover, this study tackles the challenge of differentiating between broadcast and viral information diffusion on X, acknowledging the possibility of genuine information also being potentially misleading. …

Predicting 30-Day Unplanned Icu Readmissions Using Deep Learning And Natural Language Processing Techniques: A Mimic Iv Data Analysis, David Licerio

Computational and Data Sciences (MS) Theses

We design and implement a multi-stage modeling approach focused on predicting unplanned 30-day all- cause intensive care unit (ICU) hospital readmissions using the Medical Information Mart for Intensive Care (MIMIC IV) dataset. Structured data consisting of demographic information, comorbidities, lab results, and vital signs are combined with features extracted from medical text data consisting of patients’ diagnoses, procedures, and discharge notes and further engineered using several methods, including Latent Dirichlet Allocation (LDA), Latent Semantic Analysis (LSA), and word embeddings.

We sequentially implement three distinct Dense Neural Networks (DNNs) combined with the LightGBM gradient-boosting framework. Our model attained a 5-fold cross-validated …

Traffic Analysis Of Cities In San Bernardino County, Sai Kalyan Ayyagari

Electronic Theses, Projects, and Dissertations

This research offers an in-depth analysis of vehicular traffic within San Bernardino County, California, aiming to spotlight congestion areas and suggest improvements for more efficient and sustainable transportation. Leveraging 2021 data from StreetLight Data, traffic patterns in 15 key cities were examined based on their population sizes, covering various vehicle types to dissect dynamics and flow. The methodology focused on analyzing trip purposes and metrics to calculate Vehicle Miles Traveled (VMT) and its influence on congestion and environmental factors.

Findings indicate considerable disparities in traffic volume, purposes, and timings across different urban areas, with population density and intercity connections significantly …

Truck Traffic Analysis In The Inland Empire, Bhavik Khatri

Electronic Theses, Projects, and Dissertations

This study undertakes a meticulous examination of truck traffic within the Inland Empire, focusing on the distribution and dynamics of medium and heavy-duty vehicles, to advocate for the region's transition to electric trucks. Utilizing advanced spatial analysis and data from Streetlight Data, it segments the region into six subregions, revealing distinct traffic patterns and environmental impacts. Notably, the research uncovers that the North Center and West zones, integral to the logistics and warehousing sectors, exhibit the highest traffic volumes, significantly influencing air quality and infrastructure.

Quantitative results from 2021 illustrate a pronounced disparity in truck activity: medium-weight vehicles accounted for …

Interpreting Shift Encoders As State Space Models For Stationary Time Series, Patrick Donkoh

Electronic Theses and Dissertations

Time series analysis is a statistical technique used to analyze sequential data points collected or recorded over time. While traditional models such as autoregressive models and moving average models have performed sufficiently for time series analysis, the advent of artificial neural networks has provided models that have suggested improved performance. In this research, we provide a custom neural network; a shift encoder that can capture the intricate temporal patterns of time series data. We then compare the sparse matrix of the shift encoder to the parameters of the autoregressive model and observe the similarities. We further explore how we can …

Multimodal Stylometry: A Novel Approach For Authorship Identification., Glory O. Adebayo

Electronic Theses and Dissertations

This dissertation introduces multimodal stylometry, a novel approach to authorship identification that integrates text and source code features for a comprehensive understanding of an author's unique style. Traditional stylometric methods have primarily focused on either text stylometry or source code stylometry, thereby neglecting the potential insights that multimodality may provide. This research aims to bridge this gap by proposing a framework that combines textual and source code data to enhance the accuracy and reliability of authorship identification. The study begins by reviewing existing literature on authorship identification and stylometry, highlighting the limitations of unimodal approaches. Leveraging recent advancements in multimodal …

Computational Linguistics And Multilingualism: A Comparative Analysis With Spanish And English Data, Evelyn Lawrie

Student Scholar Symposium Abstracts and Posters

Computational linguistics is an increasingly ubiquitous field, serving as the basis for artificial intelligence and machine translation. It aims to analyze the syntax and semantics of individual words and phrases. While there have been in-depth advancements in computational linguistics strategies for the English language, others have not been developed as thoroughly. This lack of emphasis on multilingualism has contributed to the disappearance of Hispanic perspectives in the digital world. Especially those of indigenous heritage, as the decline of many indigenous languages has been exacerbated by the lack of digital translation services. Sentiment analysis is a branch of computational linguistics that …

Representation Learning For Generative Models With Applications To Healthcare, Astronautics, And Aviation, Van Minh Nguyen

Theses and Dissertations

This dissertation explores applications of representation learning and generative models to challenges in healthcare, astronautics, and aviation.

The first part investigates the use of Generative Adversarial Networks (GANs) to synthesize realistic electronic health record (EHR) data. An initial attempt at training a GAN on the MIMIC-IV dataset encountered stability and convergence issues, motivating a deeper study of 1-Lipschitz regularization techniques for Auxiliary Classifier GANs (AC-GANs). An extensive ablation study on the CIFAR-10 dataset found that Spectral Normalization is key for AC-GAN stability and performance, while Weight Clipping fails to converge without Spectral Normalization. Analysis of the training dynamics provided further …

Evaluation Of An End-To-End Radiotherapy Treatment Planning Pipeline For Prostate Cancer, Mohammad Daniel El Basha, Court Laurence, Carlos Eduardo Cardenas, Julianne Pollard-Larkin, Steven Frank, David T. Fuentes, Falk Poenisch, Zhiqian H. Yu

Dissertations and Theses (Open Access)

Radiation treatment planning is a crucial and time-intensive process in radiation therapy. This planning involves carefully designing a treatment regimen tailored to a patient’s specific condition, including the type, location, and size of the tumor with reference to surrounding healthy tissues. For prostate cancer, this tumor may be either local, locally advanced with extracapsular involvement, or extend into the pelvic lymph node chain. Automating essential parts of this process would allow for the rapid development of effective treatment plans and better plan optimization to enhance tumor control for better outcomes.

The first objective of this work, to automate the treatment …

Design And Application Of Smart Systems To Address Analytical Problems, Lucas B. Ayres

All Dissertations

This dissertation is a multidisciplinary effort that integrates low-cost analytical instrumentation, redox chemistry, and artificial intelligence to overcome existing limitations in the fields of wearable sensing technology, Deep Eutectic Solvents (DES), and antioxidant chemistry. The overall goal behind each implemented strategy is to enhance the accuracy, efficiency, and accessibility of analytical processes and technologies. A general overview of the thesis, along with the research outcomes is included in Chapter One. The theoretical framework of this dissertation is presented in Chapter Two. Chapter Three describes the development of a wearable platform (sensor and instrumentation) to rapidly detect (~20 minutes) S. aureus …

Establishing “The Fossil Record”: A Database Of Vertebrate Paleontological Sites Across The State Of Tennessee, Sarah Mclaurine

Electronic Theses and Dissertations

Fossil localities across the state of Tennessee and the data related to those sites were compiled from Tennessee Division of Geology Bulletin 84, titled “Tennessee’s Prehistoric Vertebrates,” and stored in a Microsoft Access geodatabase housed by the Department of Collections at the East Tennessee State University Museum of Natural History located at the Gray Fossil Site. Included in the database are forms to enter new site localities, view information about those already entered, view and add data to a master faunal list for the state, view sites repository information and store and add documents that are key-word searchable from the …

A Framework That Explores The Cognitive Load Of Cs1 Assignments Using Pausing Behavior, Joshua O. Urry

All Graduate Theses and Dissertations, Fall 2023 to Present

Pausing behavior in introductory Computer Science (CS1) courses has been related to a student’s performance in the course and could be linked to a student’s cognitive load, or assignment difficulty. Having an objective measure of the cognitive load would be beneficial to course instructors as it would help them design assignments that are not too difficult. Two studies are presented in this work. The first study uses Cognitive Load Theory and Vygotsky’s Zone of Proximal Development as a theoretical framework to analyze pause times between keystrokes to better understand what types of assignments need more educational support than others. The …

Sports Science: An Entrepreneurial Venture, Nicole J. Jones

Senior Honors Projects

In sports science, ensuring maximum athlete safety and optimizing data utilization are pivotal yet leave room for further work. My project, Unbeaten SafeWare, addresses these critical issues by focusing on two primary concerns: preventing heat-related and cardiac illnesses, which are significant causes of athlete fatalities, and enhancing the transparency and utility of sports data. This initiative involves developing a shirt integrated with sensors to monitor vital signs and an athlete management system to handle data input, storage, analysis, and accessibility for athletes.

The project has advanced through the efforts of a multidisciplinary team, which includes biomedical engineering undergraduates, two faculty …

Denoising Diffusion Probabilistic Models Based Accelerated Mri, Alexander Francis Bugielski

Theses and Dissertations

Magnetic Resonance Imaging (MRI) is a cornerstone in obtaining intricate visualizations of anatomy and physiological processes within the human body. However, its extensive scan duration not only causes patient discomfort but also increases the likelihood of motion-induced artifacts in the images. To address such a challenge, this study investigates deep neural network models for reconstructing high-resolution MRI images from noisy and significantly undersampled data in a supervised learning manner. Specifically, it compares three models: a conventional U-Net, a self-attentive U-Net, and an innovative probabilistic diffusion model that builds upon the self-attentive U-Net architecture. These models are evaluated on their ability …

Code For Care: Hypertension Prediction In Women Aged 18-39 Years, Kruti Sheth

Electronic Theses, Projects, and Dissertations

The longstanding prevalence of hypertension, often undiagnosed, poses significant risks of severe chronic and cardiovascular complications if left untreated. This study investigated the causes and underlying risks of hypertension in females aged between 18-39 years. The research questions were: (Q1.) What factors affect the occurrence of hypertension in females aged 18-39 years? (Q2.) What machine learning algorithms are suited for effectively predicting hypertension? (Q3.) How can SHAP values be leveraged to analyze the factors from model outputs? The findings are: (Q1.) Performing Feature selection using binary classification Logistic regression algorithm reveals an array of 30 most influential factors at an …

Study On A Strong Polymer Gel By The Addition Of Micron Graphite Oxide Powder And Its Plugging Of Fracture, Bin Shi, Guangming Zhang, Lei Zhang, Chengjun Wang, Zhonghui Li, Fangping Chen

Faculty, Staff and Student Publications

It is difficult to plug the fracture water channeling of a fractured low-permeability reservoir during water flooding by using the conventional acrylamide polymer gel due to its weak mechanical properties. For this problem, micron graphite powder is added to enhance the comprehensive properties of the acrylamide polymer gel, which can improve the plugging effect of fracture water channeling. The chemical principle of this process is that the hydroxyl and carboxyl groups of the layered micron graphite powder can undergo physicochemical interactions with the amide groups of the polyacrylamide molecule chain. As a rigid structure, the graphite powder can support the …

Alterations In Brain Morphometric Networks And Their Relationship With Memory Dysfunction In Patients With Type 2 Diabetes Mellitus, Rye Young Kim, Yoonji Joo, Eunji Ha, Haejin Hong, Chaewon Suh, Youngeun Shim, Hyeonji Lee, Yejin Kim, Jae-Hyoung Cho, Sujung Yoon, In Kyoon Lyoo

Faculty, Staff and Student Publications

Cognitive dysfunction, a significant complication of type 2 diabetes mellitus (T2DM), can potentially manifest even from the early stages of the disease. Despite evidence of global brain atrophy and related cognitive dysfunction in early-stage T2DM patients, specific regions vulnerable to these changes have not yet been identified. The study enrolled patients with T2DM of less than five years’ duration and without chronic complications (T2DM group, n=100) and demographically similar healthy controls (control group, n=50). High-resolution T1-weighted magnetic resonance imaging data were subjected to independent component analysis to identify structurally significant components indicative of morphometric networks. Within these networks, the groups’ …

Comprehensive Analysis Of Bulk And Single-Cell Transcriptomic Data Reveals A Novel Signature Associated With Endoplasmic Reticulum Stress, Lipid Metabolism, And Liver Metastasis In Pancreatic Cancer, Xiaohong Liu, Bo Ren, Yuan Fang, Jie Ren, Xing Wang, Minzhi Gu, Feihan Zhou, Ruiling Xiao, Xiyuan Luo, Lei You, Yupei Zhao

Faculty, Staff and Student Publications

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with high probability of recurrence and distant metastasis. Liver metastasis is the predominant metastatic mode developed in most pancreatic cancer cases, which seriously affects the overall survival rate of patients. Abnormally activated endoplasmic reticulum stress and lipid metabolism reprogramming are closely related to tumor growth and metastasis. This study aims to construct a prognostic model based on endoplasmic reticulum stress and lipid metabolism for pancreatic cancer, and further explore its correlation with tumor immunity and the possibility of immunotherapy.

METHODS: Transcriptomic and clinical data are acquired from TCGA, ICGC, and GEO …

An Investigation Into The Causes Of Home Field Advantage In Professional Soccer, Paige E. Tomer

Mathematics, Statistics, and Computer Science Honors Projects

Home-field advantage is the sporting phenomenon in which the home team outperforms the away team. Despite its widespread occurrence across sports, the underlying reasons for home-field advantage remain uncertain. In this paper, we employ a range of statistical methods to explore the causal relationships of potential determinants of home-field advantage. We measure home-field advantage using match outcomes and differential metrics (e.g., differences in yellow cards received). In an attempt to narrow the research disparity between men’s and women’s sports, we utilize data from the National Women’s Soccer League (NWSL) and the English Premier League (EPL) to investigate potential causes of …