Digital Commons Network^™

Forensic Search Methods: Comparing Effectiveness And Efficiency In A Grassland Environment, Robert Brown

Honors Theses

An important aspect of death investigations is the recovery of human remains to determine crucial details such as body identity, time of death, and cause of death. Physical evidence is often moved by elements, such as water, gravity, plants, and scavengers in outdoor crime scenes, making recovery challenging. As a result, forensic scientists have created several search methods to locate dispersed human remains. Previous studies have primarily focused on predicting animal scavenging patterns, but few have compared the performance of forensic search methods in specific environments. This study addresses this area of research by assessing three common search methods in …

The Factors That Affect Usm Student Experience In The General Chemistry Classroom, Emma Dickerson

Honors Theses

Chemistry has a reputation for being a challenging discipline for many students. Enrollment in chemistry courses is much lower than that of other disciplines due to “chemophobia”, which can be caused by many aspects of chemistry.^1-2To increase enrollment in chemistry, it is important to understand how to improve the student experience in the classroom. To determine the factors that affect a student’s experience in their current chemistry class, the Chemistry Attitudes and Experiences Questionnaire (CAEQ) was adapted and given to students in General Chemistry I and II classes at The University of Southern Mississippi. Descriptive statistics, an Analysis …

Optimal Accelerated Life-Testing Plans Under Progressive Type Ii First Failure Censoring Scheme, Emmanuella Duah

Open Access Theses & Dissertations

Designing optimal accelerated life testing (ALT) plans under progressive Type-II first failure censoring involves complex computational challenges, especially when trying to balance efficiency, precision, and practicality. This research introduces a novel optimization framework aimed at determining the best test configuration that minimizes estimation uncertainty within constrained experimental conditions. We developed a tailored meta-heuristic strategy based on an enhanced Variable Neighborhood Search (VNS) algorithm, which efficiently navigates the complex landscape of censoring schemes and stress allocations. Unlike conventional methods that typically focus on simpler censoring or stress-level structures, this approach simultaneously optimizes both the censoring points and sample allocations across various …

Impact Of Magnetic Fields On Cosmic Ray Density In Molecular Clouds, Byron Jesus Encinas Velazquez

Open Access Theses & Dissertations

We investigate the effects caused by Cosmic Rays (CRs) in a Molecular Clouds (MCs) environment and the effects of varied magnetic field configurations in the core (r = 1 Pc ) of a MC. We take as initial conditions for the interstellar medium a product of various supernova explosions as injected initial perturbation and observe the evolution during the timescale of ~4.5 Myrs. We compute the CR reduction factor R as a measure of the density of a distribution of particles traveling with a guiding center along randomized field lines near the core and discuss their impact on the ionization …

A Digital Twin Approach To Job Shop Scheduling: Simulation And Optimization In Anylogic, Alan Alejandro Corral Lopez

Open Access Theses & Dissertations

In complex manufacturing environments such as job shops, machine breakdowns and maintenance activities can significantly disrupt production flow, leading to delays, bottlenecks, and reduced throughput. This thesis presents the development of a digital twin for a job shop system using AnyLogic simulation software to evaluate the effectiveness of fallback routing logic, where jobs are dynamically rerouted to alternative machines when primary machines are unavailable due to scheduled and unscheduled events. The digital twin replicates real-world job shop conditions, incorporating variable job sequences, machine-specific processing times, and both preventive and corrective maintenance schedules. Two scenarios were compared: a baseline configuration with …

Optimal Experimental Plan For Multi-Level Stress Testing Under Progressively Hybrid Censoring, David Kojo Amakye

Open Access Theses & Dissertations

Reliability analysis is essential for understanding how products perform over time, particularly in environments where failure data is limited or costly to obtain. One effective approach is multi-level stress testing, where test units are subjected to varying levels of stress to accelerate failures and extract more information within constrained timeframes. This study presents a novel optimization-based framework for designing life-testing experiments under progressively Type-II hybrid censoring, assuming Weibull lifetime distributions. Leveraging a Variable Neighborhood Search (VNS) algorithm, we determine efficient allocations of test units and censoring parameters across multiple stress levels to enhance the precision of estimates of the model …

Computational Framework For Integrating Single Nucleotide Variant Scores To Identify Novel Genes In Cancers, Amanda Maria Bataycan

Open Access Theses & Dissertations

A quantitative integrated scoring function, iQ(G) was developed to assess the cumulative effects of nonsynonymous single nucleotide variants (SNVs) on the protein-coding genes with the goal to find novel candidate cancer-related genes from patients with acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), and ovarian cancer (OC). With Genomic Data Commons as primary data resource for this project, whole-exome SNV data were extracted on patients with one of these three cancers. For each specific cancer, the iQ(G) function sums up the deleterious effects of individual SNVs with respect to the transcripts of the gene G in which they occur, weighted …

On The Non-Reductive Analogical Language Of Chemistry: Visualizing Chemistry As An Aesthetic Practice, Demetrio Hernandez

Open Access Theses & Dissertations

In this thesis, I will consider in detail the analogical language of chemistry by identifying metaphysical assumptions and interpretations embedded in the thinking and communication of chemistry. I will explain the epistemological function and meaning of chemical symbolism and how its artistic design presents a unique opportunity to reflect about the philosophical aesthetic connections between chemistry and the humanities. I will thus consider the creative aspects of chemistry and suggest that the merging between art and science yields practical wisdom. My goal is to argue in favor of the idea of complementarity which suggests that scientific models best develop from …

A Profile Wald Test In M-Estimation, Reagan Kesseku

Open Access Theses & Dissertations

Despite the growing popularity of machine learning-based inference, classical statistical inference remains highly relevant in modern data science due to its interpretability and theoretical rigor. Among its core tools, the likelihood ratio test, Wald test, and score test are foundational methods for hypothesis testing within the maximum likelihood framework. Although these tests are asymptotically equivalent under regularity conditions, each offers distinct advantages depending on the context, computational demands, and the availability of parameter estimates. In this dissertation, we introduce a fourth method, the Profile Wald Test (PWT), within the broader M-estimation framework. The PWT is based on profile estimators of …

Electrodeposition Of Gallium Nitride_Unraveling The Role Of Precursors, Deposition Conditions, And Substrate Effects For Semiconductor Applications, Mauricio Azier Leyva Aranzabal

Open Access Theses & Dissertations

Gallium nitride (GaN) is a wide-bandgap semiconductor noted for its remarkable optoelectronic and structural characteristics, rendering it a potential material for high-power, high-frequency, and optoelectronic device applications. This dissertation investigates the electrochemical synthesis of GaN thin films by potentiostatic and galvanostatic electrodeposition techniques using aqueous solutions of gallium nitrate (Ga(NO3)3), ammonium nitrate (NH4NO3), and auxiliary agents like potassium nitrate and urea. The main aim is to examine the essential elements affecting nitrogen incorporation and film shape while assessing electrochemical performance on various conductive substrates.A thorough investigation was performed to evaluate the impacts of electrodeposition duration, electrolyte pH, precursor molar concentrations, …

From Text To Utility: Distance-Aware Contrastive Learning For Detection-Ready And Shareable Malware Descriptions, Ivan Alejandro Montoya Sanchez

Open Access Theses & Dissertations

The rapid rise of sophisticated malware variants poses significant challenges for cybersecurity analysts, particularly due to the scarcity of data on newly emerging threats. Due to privacy, legal, and operational constraints, malware samples are often not shareable; instead, organizations publish cyber threat intelligence (CTI) in natural language. However, these reports are typically unstructured and inconsistent, limiting their utility in machine learning (ML) models. This thesis explores whether high-fidelity, shareable threat intelligence can be automatically generated from structured malware behaviors to supplement ML models when direct access to malware samples is limited. Two central questions are addressed:(i) How can descriptions be …

Computing Optimal Multi-Level Stress Testing Plans Using A Combined Variable Neighborhood Search Algorithm Under Progressive Type-Ii Censoring Scheme, Michael Obuobi

Open Access Theses & Dissertations

In multi-level stress life tests under Type-II progressive censoring, determining optimal allocation poses significant computational challenges due to the vast solution space. Efficient methods are essential for exploring the admissible censoring schemes effectively. This thesis introduces a novel meta-heuristic algorithm, the Combined Variable Neighborhood Search (CVNS), which computes optimal schemes at different stress levels simultaneously. Unlike methods focusing on marginal stress levels or one-step progressive censoring, this approach leverages a unified framework to ensure enhanced computational efficiency and solution quality. By integrating the components of the design parameters into a cohesive optimization process, the algorithm effectively reduces computational time while …

Clinicogenomic Insights For Prostate Cancer Progression, Kelvin Ofori-Minta

Open Access Theses & Dissertations

Prostate cancer (PrCa) remains a critical challenge in precision oncology due to several reasons including its apparent heterogenous condition, recurrence following treatment and rapid progressive forms. Therefore, identifying patients at risk of progression is essential to fast-track therapeutic decisions and improve outcomes. Despite recent advances in genomic and molecular profiling, conventional PrCa risk assessment tools heavily rely on a few clinical parameters, neglecting the prognostic potential of genomic biomarkers in the presence of clinical biomarkers. This study presents a computational pipeline to harmonize and evaluate the prognostic value of clinicogenomic profiles of patients in modelling progression free survival (PFS). PFS, …

Towards Mitigation Of The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Jaime Merin Guzman

Open Access Theses & Dissertations

Detecting and localizing faults in communication networks is critical to maintaining reliable and efficient network operations. The Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm has demonstrated its potential to automate this task but suffers from significant performance degradation under low network load conditions, where limited network flow data reduces its ability to localize faults. This thesis proposes and evaluates the performance of a synthetic traffic generation algorithm to be used with NLOF:MLL. This algorithm strategically injects synthetic flows that supplement the insufficient real network flows, thereby improving NLOF:MLL's performance under low-load conditions. Specifically, we select network …

Development Of Saddlepoint Methodologies For Sparse Sample Multiple Parameter Generalized Linear Models And Correlated Data Scenarios, Christopher Johnson

All Graduate Theses and Dissertations, Fall 2023 to Present

Parameter estimation using maximum likelihood techniques may be biased when sample sizes are small, event rates are low, or otherwise sparse counts exist in a parametric model. This in turn may lead researchers to draw invalid statistical conclusions when conventional methods are utilized. The saddlepoint approximation has potential to lessen the degree of bias in sparse data conditions through its use of moments beyond the mean and variance, which allows for more accurate approximations using a smaller number of observations. We propose two novel saddlepoint methods for use in practical analysis scenarios, as an alternative to maximum likelihood estimation. First, …

Learning Intentions, Success Criteria, And Metacognition: The Influence Of A Professional Development For Grades Three To Five Teachers, Jason Hart

All Graduate Theses and Dissertations, Fall 2023 to Present

Formative assessment is a strategy that teachers use to improve student learning. This study explored how professional development focused on assessment for learning practices (AFL), with the main emphasis on learning intentions and success criteria, influences teacher use of those strategies and changes in teacher and student metacognition. The overarching research question was: How does professional development on AFL practices influence teachers' reported use of AFL practices and teacher and student metacognition? This study utilized a mixes-methods research design and provided professional development on AFL practices to 16 in-service elementary mathematics teachers and measured changes to their AFL practices and …

A Comparison Of Principal Motivational Orientation And The Orientation Of Principal Actions To Motivate Teachers, Charles K. Stewart

All Graduate Theses and Dissertations, Fall 2023 to Present

This study was planned and conducted to evaluate the correlation between a principal’s dominant motivation type (intrinsic or extrinsic) related to their dominant method to motivate others (intrinsic or extrinsic). The study included nine elementary school principals who led schools to high levels of academic performance. Three participating principals were selected from a school with high poverty rates. Three other principals were selected from schools with medium poverty rates, and three more were selected from schools with low poverty rates.

The researcher collected information from the nine participating principals regarding factors that motivate them to improve student learning at their …

Determining The Structure And Function Of Type Iv-A Anti-Crisprs, Olivine Redman

All Graduate Theses and Dissertations, Fall 2023 to Present

Bacteria face a constant existential threat in the form of infection by viruses along with other forms of mobile genetic elements, such as bacteriophage and transposable elements. To survive, bacteria and other prokaryotes have evolved various immune systems to evade these would-be invaders. One such immune system is the CRISPR-Cas system, an adaptive immune system able to record the genetic signature of invading viruses in order to recognize and destroy them should they be encountered again in the future. In this thesis I present data that sheds light on the mechanism of one particular subtype of CRISPR-Cas systems: the type …

A Survey Of Master's Qualifying Exam Practices And Content In Real Analysis, Zachary M. Coverstone

All Graduate Theses and Dissertations, Fall 2023 to Present

Graduate programs in mathematics are intended to develop experts in mathematics. As part of a graduate program, many students are expected to engage in a qualifying examination that can serve myriad purposes. This dissertation investigates real analysis qualifying examinations at the master's level through a nation-wide survey of institutions in the Association of Public and Land-Grant Universities (APLU). This study reveals the practices in administration of real analysis qualifying exams, institutions reported offering traditional, pencil-and-paper exams and generally asked students to prepare individually using previously administered exams. The survey results show that approximately two in three APLU institutions offering master's …

Investigating Stability Of Cone-Derived Hypersonic Waverider Vehicles Via Design Space Exploration, Adam S. Weaver

All Graduate Theses and Dissertations, Fall 2023 to Present

It may come as no surprise that man-made objects flying at 5, 10, or even 25 the speed of sound (termed hypersonic) are difficult to design, inefficient in flight, and expensive to deploy. Most hypersonic vehicles are effectuated in ballistics, which simplify aerodynamic considerations owing to their fixed trajectory. However, maneuverable hypersonic vehicles can revolutionize commercial flight, national defense, and space travel. One candidate for such missions are waverider vehicles. Waverider vehicles cruise on a cushion of air generated by its own shock wave, essentially enjoying extra lift without any extra drag penalties (which are usually inherent to extra …

Increasing The Spatial Resolution Of Snow Hydrology Data And Augmenting Existing Hydrology Monitoring Networks Using Low-Cost Snow Sensing Stations, Braedon Dority

All Graduate Theses and Dissertations, Fall 2023 to Present

Snow is a crucial part of the water cycle, especially in mountainous regions where melting snow provides water for millions of people. However, accurately measuring how much water is stored in snow is challenging. Current monitoring networks, such as the snowpack telemetry (SNOTEL) network in the western United States, provide valuable data, but have gaps in coverage and are expensive to operate and expand. This research explores a more affordable way to improve snow measurements by designing and testing low-cost snow sensing stations. These stations use open-source datalogger and software technology along with research-grade sensors to measure important snow variables. …

Surface Vortex Mitigation At Submerged Intakes, Camren Todd

All Graduate Theses and Dissertations, Fall 2023 to Present

Surface vortices at submerged intakes entrain air, convey debris, and reduce efficiency. This research investigates the effect of lid geometry on mitigation of surface vortices at submerged intakes in the context of still reservoirs. Six lid geometries were evaluated: three solid lids of increasing diameter, two lids with perforations, and one lid fitted with a downward curtain. Vortex severity was measured by Alden’s vortex type rating scale, surface-dimple diameter, and qualitative video analysis.

The perforated lid extension and the curtain configurations were most effective at mitigating vortices. The curtain configuration negated all surface swirling by redirecting a portion of the …

Blind Construction Of A Party Check Matrix For Arbitrary Linear Block Codes, Aaron J. Womack

All Graduate Theses and Dissertations, Fall 2023 to Present

Communication systems are systems in which a transmitter sends data across a channel to a receiver. In any modern communication system, Forward Error Correction (FEC) is used to detect and correct errors that occur during transmission. As communication systems have developed over the years, many FEC algorithms have been proposed. Each FEC algorithm has parameters that can be selected based on the needs of the communication system. Typically, the transmitter and receiver are both aware of the FEC parameters, but in some cases the receiver may not know how the transmitter encoded its message. In this case, the receiver must …

Conservation Laws For Asymptotically Perfect Fluid Spacetimes, Lyle Arnett Jr.

All Graduate Theses and Dissertations, Fall 2023 to Present

In physics, conservation laws, like those for energy or momentum, are powerful tools that help us understand how systems evolve and interact. In general relativity, where spacetime itself is curved by matter and energy, defining such conservation laws becomes especially subtle and complex. Traditional methods rely on idealized conditions like empty space or special symmetries, which limit their usefulness in more realistic, dynamic settings such as an expanding universe.

This dissertation explores a modern mathematical framework, developed by Iyer and Wald, that allows conservation laws to be derived directly from the equations governing spacetime. Using this approach, I examine not …

Hidden Layer Reshaping On Convolutional Neural Network, Alan Delgado

Open Access Theses & Dissertations

Artificial Intelligence (AI) technologies have become really popular in recent years. From ChatGPT to Tesla cars, many applications can benefit from these type of technologies. Automotive, healthcare, biomedical, cybersecurity, finances, and retail are some of the fields that take advantage of it. It has been seen that AI can solve complex problems, but there is still work to be done to optimize it. A deep learning neural network (DLNN) tries to simulate how a human brain operates. These DLNNs are made up of artificial neurons which are connected by weight that are modified when the network is trained. These networks …

Development Of Porous Separators For Lithium-Ion Batteries Via 3d Printing And Thermally Induced Phase Separation, Abraham Enchinton

Open Access Theses & Dissertations

Additive manufacturing processes allow the development of custom-shape rechargeable batteries, but research in custom filaments for fused deposition modeling (FDM) of battery separators has remained limited until now. This study discusses the development and optimization of a composite thermoplastic filament feedstock to 3D print separator membranes. A number of post-processing steps - leveraging the thermally induced phase separation (TIPS) of the composite filament - are introduced in tandem with FDM to promote microporosity formation through the removal of the sacrificial diluent phase within 3D printed samples. Three distinct compositions of varying polymer/diluent ratios were developed and thoroughly investigated through thermogravimetric …

Charging Infrastructure Needs For Electric Trucks In Texas, Katerina Jilkova

Open Access Theses & Dissertations

This thesis focuses on the design of a methodology for determining the optimal location of charging stations for heavy-duty electric trucks. The work focuses primarily on long-distance trips that require charging the truck battery outside cities, where the range of charging stations is not extensive. In addition to design the algorithm, the thesis also focuses on implementing the algorithm on a specific case - the implementation of charging stations in the I-10 Freeway corridor between El Paso and San Antonio. The output of the work is not only a description of the procedure, but also an application to a real …

Computing Optimal Progressive Hybrid Censoring Schmes Using An Mcmc Type Probabilistic Approach, Irene Yemotiorkor Odoi

Open Access Theses & Dissertations

Progressive hybrid censoring schemes play a crucial role in optimizing life-testing experiments by balancing test duration and statistical efficiency. This study presents a Markov Chain Monte Carlo (MCMC)-based probabilistic approach for determining optimal progressive hybrid censoring schemes, incorporating a time-dependent component that enhances traditional progressive censoring methods.We implement our approach using three distinct probability distributions the multinomial, hypergeometric, and uniform distributions to simulate censoring schemes. The optimal censoring schemes are then identified based on three optimality criteria: A-optimality, D-optimality, and T-optimality, ensuring robust selection by minimizing estimator variance, maximizing Fisher information, and optimizing test duration, respectively..To evaluate the effectiveness of …

Investigation Of High-Frequency Electron Spin Dynamics In The Kagome-Lattice Ymn6sn6 Crystal, Lovia Ofori

Open Access Theses & Dissertations

Kagome magnetic crystals received a great deal of research attention in the recent past for their intriguing magnetic properties. Recently, YMn6Sn6 (Y166) has shown to exhibit several nontrivial magnetic phases (such as the Distorted Spiral (DS) phase, Transverse Conical Spiral (TCS) phase, Fan-like (FL) phase and the Forced-Ferromagnetic (FF) phase) and complex magnetic interactions. In this work, we employed very high-frequency electron paramagnetic resonance (VHF-EPR) spectroscopy to investigate the local microscopic magnetic interactions of Mn ions in the Kagome Crystal Y166 to better understand the new observed magnetic phases. Particularly, we studied the temperature-dependent EPR behavior at variable very-high microwave …

From Land To Lagoon: The Spatiotemporal Biogeochemical Dynamics Of Arctic Coastal Erosion In Elson Lagoon, Alaska, Sasha Victoria Peterson

Open Access Theses & Dissertations

TThe Arctic is warming rapidly, driving widespread environmental change across coastal landscapes, including permafrost thaw, shoreline erosion, and shifts in sediment and carbon dynamics, pose growing challenges for predicting carbon cycling and climate feedbacks. This dissertation investigates the spatiotemporal variability of erosion, decomposition, and nearshore turbidity in Elson Lagoon, Alaska (1955–2023), to better understand how carbon, nitrogen, and sediment are mobilized, transformed, and potentially emitted as greenhouse gases in Arctic coastal systems. Chapter 2 presents a high-resolution analysis of shoreline change and erosion-driven material fluxes spanning nearly seven decades. Drawing on 795 soil data points, airborne LiDAR, and five shoreline …