Digital Commons Network^™

Integrating Data Management Plans Into The Unified Architecture Framework Standards Views, Cansu Yalim, Holly A. H. Handley

Engineering Management & Systems Engineering Faculty Publications

System Architecting translates an operational concept into a model of the system to be realized. There is a need for a Data Management Plan (DMP) to be included in the overall system engineering process with the advent of Digital Engineering. Data longevity, accessibility, and integrity can all be improved throughout the system's lifecycle by a well-defined DMP. System engineers use an architecture framework to arrange the system data into several sets of viewpoints. Incorporating a DMP at this point specifies the procedures for gathering, storing, retrieving, and maintaining data to ensure that all interested parties have access to current, correct …

Artificial Intelligence In Radiology, Olivia Sweeney

Theses, Dissertations and Capstones

Introduction: Artificial intelligence (AI) has increasingly transformed radiologic practice by improving diagnostic accuracy, streamlining workflows, and reducing interpretation errors. As AI integration has expanded across imaging modalities, questions have emerged regarding its effectiveness compared to traditional radiologist-only interpretation.

Purpose of Study: The purpose of this study has been to evaluate the impact of AI-assisted radiology on diagnostic accuracy, efficiency, and error reduction, while also assessing clinician perceptions of AI as a collaborative tool in imaging analysis.

Methodology: This qualitative study has used a systematic review of peer-reviewed literature published between 2015 and 2025, following PRISMA guidelines, combined with an interview …

Sedimentary Archives Of Late Quaternary Limnological, Ecological, And Environmental Change In The Eastern Sierra Nevada (California, Usa), Bailee Hodelka

Theses and Dissertations--Earth and Environmental Sciences

The Sierra Nevada essentially serve as the headwaters of California, providing crucial freshwater to the state through seasonal snowmelt. This water supply is threatened by climate change in complex ways that are not fully understood. Geological records provide a valuable source of information on how the hydrology, limnology, and ecology of the Sierra Nevada region has responded to climate changes of the past. This dissertation presents new sedimentary and paleoecological research from Mono Lake and Convict Lake (Mono County, California) and aims to shed light on environmental changes in the eastern Sierra Nevada from ~16 ka to present.

At Mono …

Interaction Mechanism Between Health Anxiety And Information Seeking Behavior From The Perspective Of Phenomenology, Yanfeng Zhang, Minqian Yu

Journal of Scientific Information Research

[Purpose/significance]To analyze the evolution characteristics of health anxiety before and after information search behavior from the perspective of phenomenological graph analysis, and to explain the internal mechanism of the interaction between health anxiety and information search behavior. [Method/process]By using the phenomenological qualitative research method, the interactive mechanism between health anxiety and information search behavior was deeply explored. Based on the I-PACE theoretical model framework, the model elements of users' health anxiety and information search behavior were analyzed from the four dimensions of "Person-Affect-Cognition-Execution". To construct a mechanistic relationship model between health anxiety and information search behavior. [Result/conclusion]The research results revealed …

Sustainable Water Purification Using Green-Synthesized Nanoparticles: A Comparison Between Mono- And Bimetallic Nanoparticle Systems, Sai Bhargava Vipparla, Naveen Debbata, Satyavardhan Dharmapuri, Anil Kumar Busi, Pranay Bhasker Kalakonda, Dayanand Aitipamula, Moses Kigozi, Pritam Mandal, Krishna Kumar Balu, Parvathalu Kalakonda

Michigan Tech Publications

This review explores recent advancements in using environmentally benign monometallic nanoparticles (MMNPs) and bimetallic nanoparticles (BMNPs) for photocatalytic water purification, addressing the urgent need for sustainable solutions to global water scarcity. This study systematically analyzes how key photocatalysis variables, including nanocatalyst concentration, dye selection, and pollutant concentration, influence dye degradation outcomes. Standardized experimental conditions utilizing UV irradiation, 10 ppm, methylene blue (MB), and green synthesis routes were employed for comparative assessment. Results indicate that BMNPs, particularly Ag-Cu BMNPs composites, consistently outperform their MMNPs, achieving degradation rates between 90% and 99%, compared to 70%–85% for MMNPs. This superior performance is attributed …

Deep Learning-Based Ensemble Two-Step Classification Of Medical Images Using Cnn Architectures And Ensemble Methods, Noreliz Alorico

Master's Theses or Doctor of Nursing Practice

Breast cancer remains one of the most common cancers amongst women globally. Early detection is crucial for improving survival rates. While mammography is widely used and an effective imaging technique, it can sometimes yield false positive or false negatives. Mammogram interpretation is highly operator-dependent, introducing variability and the potential for diagnostic errors. Additionally, mammographic images have limitations, such as low contrast in breast tissue and overlapping structures that can obscure lesions or mimic abnormalities. These limitations can lead to unnecessary biopsies or delayed diagnosis. These challenges highlight the needs for advanced and data driven diagnostic tools to support and enhance …

Towards Smart Farming: Image-Based Crop Health Assessment And Disease Diagnosis Using Deep Learning Techniques, Kristina Botova

Master's Theses or Doctor of Nursing Practice

Accurate crop monitoring is essential for optimizing agricultural productivity and ensuring food security. This study presents a comprehensive deep learning framework for image crop type recognition, health status prediction, and disease detection using multiple Convolutional Neural Network (CNN) models. The proposed approach uses open-source datasets consisting of five crop types (apple, corn, grape, potato, tomato), varying health conditions, and common diseases. By deploying specialized CNN architecture focused on each task, the system achieves a high accuracy of 99.25% in classifying crop types, identifying health status, and detecting specific diseases. Compared to a single CNN model, the use of the proposed …

Swosu Research And Scholarly Activity Fair 2025, Swosu Office Of Sponsored Programs

SWOSU Research and Scholarly Activity Fair Programs

On behalf of the members of the University Research and Scholarly Activity Committee (USRAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University (SWOSU) — welcome to the Thirty-Third SWOSU Research and Scholarly Activity Fair!

This year’s event features 99 poster presentations and 9 oral presentations, showcasing the work of over 170 student and faculty researchers, writers, presenters, artists, collaborators, and faculty sponsors. These presentations represent a wide array of scholarly and academic activity from across SWOSU’s academic community, including the Departments of Art, Communication, and Theatre; Allied Health Sciences; Biological Sciences; Business; Chemistry & …

The Knowwheregraph Ontology, Cogan Shimizu, Shirly Stephen, Adrita Barua, Ling Cai, Antrea Christou, Kitty Currier, Abhilekha Dalal, Colby K. Fisher, Pascal Hitzler, Krzysztof Janowicz, Wenwen Li, Zilong Liu, Mohammad Saeid Mahdavinejad, Gengchen Mai, Dean Rehberger, Mark Schildhauer, Meilin Shi, Sanaz Saki Norouzi, Yuanyuan Tian, Sizhe Wang, Zhangyu Wang, Joseph Zalewski, Lu Zhou, Rui Zhu

Computer Science and Engineering Faculty Publications

KnowWhereGraph is one of the largest fully publicly available geospatial knowledge graphs. It includes data from 30 layers on natural hazards (e.g., hurricanes, wildfires), climate variables (e.g., air temperature, precipitation), soil properties, crop and land-cover types, demographics, and human health, various place and region identifiers, among other themes. These have been leveraged through the graph by a variety of applications to address challenges in food security and agricultural supply chains; sustainability related to soil conservation practices and farm labor; and delivery of emergency humanitarian aid following a disaster. In this paper, we introduce the ontology that acts as the schema …

A Study Of User Experiences Of Pediatric Physicians With Electronic Health Record Systems: Encounters With Task Complexity And Efficiency Of User Task Flows, Roseanne Alhindi

CCAC Theses and Dissertations

way patient information is stored, managed, and accessed. This transition to Electronic Health Record (EHR) systems has enhanced the efficiency and accuracy of healthcare delivery by enabling quick access to patient records, reduction of errors, and facilitation of coordination among healthcare providers. In the EHR system, diverse tasks are performed for clinical processes and patient care. These tasks can be considered simple or complex, ranging from documenting patient visits and updating medical histories to ordering tests and managing prescriptions. Although EHR systems have become more prevalent in their use, there are noted challenges associated with the design of the system …

Navigating Wastewater: Minnesota Mining Wastewater Permit Challenges And Evolving Compliance Standards, Madelaine Adamich

Journal of Earth and Life Science

February of 2021 marked the beginning of Minnesota clearly establishing that groundwater qualifies as a Class 1 water in a legal battle involving United States Steel, the Minnesota Pollution Control Agency, WaterLegacy, Fond du Lac Band of Lake Superior Chippewa, the Minnesota Court of Appeals, and eventually the Minnesota Supreme Court (MNSC). Minnesota has a water classification system, as required by the federal Clean Water Act, with 7 classes of use. Class 1 waters are waters used for domestic consumption (MPCA 4, n.d.). According to Minnesota Statute § 7050.0220, the acceptable level for sulfate is 250 mg/L in Class 1 …

Aquatic Invertebrate Populations In Roadside Wetlands In Relation To Water Characteristics, Ellen P. Isakson

Journal of Earth and Life Science

The continual habitat destruction and draining of wetland systems makes the need to understand the ecology of roadside wetlands all the more necessary. Roadside wetlands provide valuable habitat to countless aquatic invertebrates, which can provide insight into the health of the wetland system due to their diversity. The objective of this study was to analyze the populations of aquatic invertebrates in roadside wetlands in relation to water characteristics such as pH, salinity, conductivity, water depth and temperature, and dissolved oxygen. This was done by collecting samples of invertebrate populations from roadside wetlands, in addition to data on water quality characteristics …

Usu Extension Sustainability Permaculture Initiative: 2025 Impact Report, Natalia Bustos, Roslynn Brain Mccann, Jake Powell

Extension Research

• Permaculture Statistics
• Harvest Donations (Organic)
• Participant Response
• 2025 Monthly Educational Events
• Publications
• USU Extension Workshops & Events

Chromium Removal From Tannery Wastewater Via A Hydroponic Technique With Vetiver Grass (Vetiveria Zizanioides), Ismot Zereen, Zainul Abedin, Siddikur Rahman, Debasish Pandit

Applied Environmental Research

This research aimed to investigate the effects of hydroponically cultivated vetiver grass (Vetiveria zizanioides) on the treatment of tannery wastewater for chromium (Cr) removal in Bangladesh. The field experiment involved 9 containers, which were separated into 3 groups: tannery wastewater with hydroponically planted vetiver, tannery wastewater without vetiver (control), and a group with vetiver grown in tap water. The tap water group was used solely for plant growth assessment, whereas only the control and hydroponic vetiver groups were evaluated for Cr and water quality parameters. Throughout the 45-day trial period, Cr and other water quality parameters were analyzed …

Government Support And Local Residents’ Behavior In E-Waste Management: Evidence From Thailand, Peeranart Kiddee, Somsiri Decharat, Suttiporn Bunmak

Applied Environmental Research

Electronic waste (e-waste) management is a critical global pollution concern. This study investigates government support; local residents' perceptions, knowledge, attitudes, and behaviors related to e-waste management; and collaborative governance in southern Thailand. Employing both quantitative and qualitative methods, this research involves expert government officers who are well versed in e-waste management and local residents. The study utilized in-depth interviews, questionnaires, and workshops. The results revealed that the government is responsible for four e-waste management approaches, encompassing various e-waste collection, transportation, and disposal methods. Local residents exhibited low perceptions of e-waste news but possessed substantial knowledge and positive attitudes toward e-waste …

Exploring The Co-Composting Potentials Of Raw Grease Trap And Grease Trap-Derived Soaps: Insights Into Grease Trap Modification, Calcium Supplementation, And Microbial Community Analysis, Pokchat Chutivisut, Panaya Kotchaplai, Bualuang Faiyue, Nattapong Tuntiwiwattanapun

Applied Environmental Research

Managing waste with grease traps poses a challenge because of the potential environmental issues associated with its disposal. In this study, two approaches were investigated to increase the biodegradability of grease trap waste: 1) converting raw grease trap waste into soap and 2) supplementing grease trap soap as inoculum with calcium material. The preparation of grease trap soap was optimized to attain a soap yield of 103% by utilizing a water-to-ethanol ratio of 9:1 at 80 °C for a processing time of 3 hours. A comparison of the composting results revealed higher nitrate yields with increased ratios of grease trap …

Microplastic Contamination In Commercially Important Bivalves Of Sorsogon Bay, Philippines, Sarina M.B. Arciga, Charmaine A. Malon, Kenneth N. Ballaran

Applied Environmental Research

Sorsogon Bay, a key fishing ground in the Philippines, is known for its commercially important bivalve species: Perna viridis, Atrina pectinata, and Paphia undulata. Despite their ecological and economic value, limited research has been conducted on microplastic contamination in bivalves harvested from this area. This study aimed to assess the abundance and types of microplastics in commercially important bivalves (P. viridis, A. pectinata, and P. undulata) from Sorsogon Bay, Philippines. Commercial bivalve samples were randomly collected, digested with 10% w/v potassium hydroxide (KOH) solution, filtered (8 µm), and examined under a compound microscope. …

Landslide Susceptibility Mapping Via Dempster-Shafer, Statistical Index, And Certainty Factor Models In Gis And Their Comparison At Pidie Recency In Aceh, Indonesia, Septianto Aldiansyah, Amniar Ati, Fitriyani Saudi

Applied Environmental Research

Landslides are natural disasters that are active if there is an interaction of environmental factors that are considered to control them, especially in mountainous areas. This study developed a landslide susceptibility map in Pidie Regency via the Dempster-Shafer (DS), statistical index (SI), and certainty factor (CF) models. A total of 957 landslide events were mapped, 70% of which were used for modeling, whereas the remaining events were used to validate the model output. Fourteen layers of conditioning factors were used: elevation, slope, aspect, curvature, TWI, SPI, STI, NDVI, rainfall, distance from river, distance from road, distance from fault, LULC, and …

Assessment Of Landslide Susceptibility And Settlement Exposure Via Geospatial Techniques In Bulambuli Distrcit, Eastern Uganda, Andrew Mulabbi, John Calvin Esagu, Gertrude Akello, Remigio Turyahabwe

Applied Environmental Research

Landslide susceptibility is a significant concern in Elgon County, Uganda, particularly during the rainy season. This vulnerability is attributable to several factors, including steep slopes, fertile soils, and dense settlements on volcanic ridges. Landslide susceptibility maps are important in mitigating the risk particularly at the local level. The objectives of this study were 1) to model landslide susceptibility via an interpretable machine-learning model, 2) to identify the most influential factors for landslide susceptibility in the study area, and 3) to assess the exposure of settlements to landslide risk. This study employed the XGBoost model trained on nine conditioning factors via …

Exploration Of Indigeneous Biosurfactant-Producing Bacillus Sp. From Petroleum Hydrocarbon-Contaminated Soil In Indonesia, Rizky Danang Susetyo, Wahyu Wilopo, Suwarno Hadisusanto, Endah Retnaningrum

Applied Environmental Research

Hydrocarbonolastic bacteria are valuable for the remediation of petroleum-polluted environments. The production of biosurfactants by such bacteria significantly enhances hydrocarbon bioavailability and increases remediation efficiency. One genus of hydrocarbonolastic bacteria with the potential to produce biosurfactants is Bacillus, yet strain-level diversity and local adaptations remain underexplored.Tthis study aimed to isolate and characterize hydrocarbonolastic bacteria belonging to the Bacillus genus from soil samples collected at Geopetroleum Teksas Wonocolo, Kedewan District, Bojonegoro Regency, Indonesia, which is a historically underreported hydrocarbon site. Additionally, the capacity of Bacillus to synthesize biosurfactants was examined. Bacillus strains capable of biosur-factant production were identified via a polyphasic …

Examining Short Term Drainage Impacts To Soil Health In Hydric And Non-Hydric Soils Of Waseca County, Minnesota, Ely Hartl

All Graduate Theses, Dissertations, and Other Capstone Projects

Subsurface drainage is implemented throughout the Midwest United States to remove excess moisture from soil to enhance crop growth. Hydric soils are ubiquitous throughout Minnesota and are commonly drained due to their historically saturated conditions. Changing a soil's hydrology can impact its formation and properties. The alteration of physical, biological, and chemical soil properties can occur to both hydric and non-hydric soils, impacting overall soil health. The purpose of this study is to examine the short-term effects of tile drainage on the soil health of hydric and non-hydric soils in southern Minnesota. Research methods include: 1) collect soil-sediment cores to …

Hydrogen Peroxide Production From Light-Driven Water Oxidation Via Nickel Oxide-Titanium Dioxide Heteronanocrystals, Mahfuz Ahammed Swadhen

Dissertations and Theses

High dependence on fossil fuels for energy carries risks for the environment, health, energy, and geopolitical stability. One of the solutions to address this is solar energy utilization, and the use of semiconductors for photocatalytic water splitting is a tantalizing prospect. An n-type semiconductor TiO2 combined with p-type NiO producing a heteronanojunction shows effective light-driven oxidation of H2O into H2O2. We developed a synthetic method to attach NiO nanoparticles on the surface of anatase TiO2 nanorods. We characterized the materials with UV-visible spectroscopy, powder X-ray diffraction, and electron microscopy. We immobilized the HNCs on fumed silica and removed organic surfactants …

Leveraging Distributed Semantics From Deep Learning Architectures For Literature-Based Discovery, Clint A. Cuffy

Theses and Dissertations

Literature-based discovery (LBD) is a scientific process that introduces methods to automatically identify novel insights between non-interacting sets of literature. To date, numerous statistical and machine learning-based methods have been applied in the biomedical domain to find treatments for diseases such as Raynaud's disease, Parkinson's disease, and Multiple Sclerosis. However, the lack of standardized practices and creation of bespoke methodologies produces a scenario where the adoption of LBD remains challenging in real-world systems. Our work addresses these concerns through the improvement of five critical areas: 1) error propagation within LBD's a priori dependent tasks, 2) exploring the integration of modern …

Beyond Homogeneity: Exploring Causal Heterogeneity In Psychopathology, Philip B. Vinh

Theses and Dissertations

Traditional models in psychiatric research often impose assumptions of causal homogeneity, treating population-level associations as reflective of uniform underlying mechanisms. This dissertation challenges that assumption by introducing statistical and machine learning frameworks designed to detect and model causal heterogeneity in the development of psychopathology. Central to this approach is the advancement of finite mixture structural equation modeling (FM-SEM) to identify latent subgroups characterized by distinct, and sometimes opposing, causal pathways.

The dissertation comprises three integrated empirical studies. The first introduces mixDoC, a finite mixture extension of the classical Direction of Causation (DoC) model applied to twin data, enabling the detection …

Modeling The Impacts Of The Current And Projected Temperatures On Spongy Moth Population Dynamics, Adrienne B. Spring

Theses and Dissertations

The spongy moth (Lymantria dispar) is an invasive forest pest that has caused significant ecological damage across the United States. Its invasion front is shaped by a number of factors, including temperature in both the northern and southern regions. With ongoing climate change, areas that were previously uninhabitable may become increasingly favorable for moth population establishment and expansion, while other areas may experience thermal stress limiting persistence. This study develops a temperature-driven population model to analyze how temperature affects the spongy moth population dynamics along the invasion front. This model incorporates temperature effects on fecundity, stage-specific survival rates, …

Evaluating Spatiotemporal Vegetation Index Variation To Detect Salt Marsh Dieback On The Georgia Coast, Emmanuella Bosompemaa Obeng

College of Graduate Studies: Theses & Dissertations

Salt marshes, essential for coastal protection and carbon sequestration, are increasingly vulnerable to dieback events, threatening ecosystem resilience and vital services. Detecting these shifts early is essential for timely intervention. However, few studies have applied Early Warning Signals (EWS) to coastal marsh systems. Most EWS research has focused on lakes, forests, or climate tipping points, with limited application to salt marsh dieback in the southeastern U.S. Site-specific, long-term spatial analyses are also lacking, as prior work often examines short time frames or single disturbance events. This study investigates the spatiotemporal patterns of salt marsh dieback on the Georgia coast from …

New Psychoactive Substances Detected In Wastewater Samples Collected Along The Interstate Highway Rest Areas In Kentucky, Durga Prasad Kodati

Murray State Theses and Dissertations

The rapid emergence and proliferation of new psychoactive substances (NPS) pose significant challenges to public health and law enforcement. The potential for abuse and toxicity of these substances, which are intended to mimic the effects of controlled drugs, has been raising concerns as these compounds are designed to evade being regulated. There are traditional methods of tracking NPS, such as seizures and forensic toxicology, but they are delayed and seldom effective because these substances continue to evolve rapidly. Wastewater-based epidemiology (WBE) has emerged as a promising tool for real-time surveillance of drug consumption. The primary objective of this research was …

Fares On Fairness: Using A Total Error Framework To Examine The Role Of Measurement And Representation In Training Data On Model Fairness And Bias, Patrick Oliver Schenk, Christoph Kern, Trent D. Buskirk

Information Technology & Decision Sciences Faculty Publications

Data-driven decisions, often based on predictions from machine learning (ML) models are becoming ubiquitous. For these decisions to be just, the underlying ML models must be fair, i.e., work equally well for all parts of the population such as groups defined by gender or age. What are the logical next steps if, however, a trained model is accurate but not fair? How can we guide the whole data pipeline such that we avoid training unfair models based on inadequate data, recognizing possible sources of unfairness early on? How can the concepts of data-based sources of unfairness that exist in the …

Robust Palm Print For Mobile Authentication System, Son Nguyen

Chulalongkorn University Theses and Dissertations (Chula ETD)

Smartphones are gateways to financial, health, and personal data; consequently, mobile authentication must be accurate, fast, privacy-preserving, and scalable. This thesis presents an end-to-end palmprint authentication framework that addresses a practical trilemma: label-efficient learning, on-device efficiency, and cloud-scale identification. We pretrain a ResNet-18 encoder with self-supervised contrastive learning on unlabeled palm images, distill its representation to a lightweight MobileNetV3 student for real-time inference on phones, and support both 1:1 on-device verification and 1:N cloud identification using FAISS/HNSW. On public datasets, the system attains 99.2% accuracy, a 0.15% equal-error rate (EER), and ~87 ms end-to-end latency on iPhone-class hardware. FAISS scales …

Artificial Intelligence And Environmental Sustainability: Review And Research Directions, Troy Strader, Yu-Hsiang (John) Huang, Yu-Ju Tu

Journal of International Technology and Information Management

Environmental sustainability is one of the most important and complex issues currently facing our global society. One solution to some aspects of this problem could come from artificially intelligent systems and data analytics methods. The objective for this study is to identify the range of recently published research that addresses issues involving the convergence of artificial intelligence (AI) and environmental sustainability. A systematic literature review produced a sample of 62 journal articles from 2018-2024 that were each categorized into one of six research themes that included studies of AI and the ways in which it impacted natural resources, energy and …