Physical Sciences and Mathematics Commons^™

Going Dark And Encryption, Brendan Funk

Mathematics and Computer Science Capstones

Law officers across the country and around the world are being left in the technological dust by their criminal counterparts. They have no problem obtaining evidence, however they run into issues accessing this information due to various encryption techniques being used. This phenomenon has been dubbed the “Going Dark” problem. James Comey describes the Going Dark problem as, “We have the legal authority to intercept and access communications and information pursuant to court order, but we often lack the technical ability to do so” (Comey, 2014).

The Going Dark problem is a relatively new problem facing law enforcement officers (LEOs) …

The Negative Economic Impacts Of Money Laundering In Kenya, Thailand And France, Peyton Tollaksen

Mathematics and Computer Science Capstones

Cybercrime has grown exponentially around the world due to consistently changing technology and the craftiness of cybercriminals often outpacing that of security officers. In the past three decades, cybercrime has been expedited and globally expanded due to the accumulated experience of these criminals, who take advantage of the new found black market, cryptocurrency, and other operations. According to a report published by the Center for Strategic and International Studies titled, “Economic Impact of Cybercrime,” it was found that, “close to $600 billion, nearly one percent of global GDP, is lost to cybercrime each year” (2018). Unfortunately, this number will only …

U-No: U-Shaped Neural Operators, Md Ashiqur Rahman, Zachary E Ross, Kamyar Azizzadenesheli

Department of Computer Science Faculty Publications

Neural operators generalize classical neural networks to maps between infinite-dimensional spaces, e.g., function spaces. Prior works on neural operators proposed a series of novel methods to learn such maps and demonstrated unprecedented success in learning solution operators of partial differential equations. Due to their close proximity to fully connected architectures, these models mainly suffer from high memory usage and are generally limited to shallow deep learning models. In this paper, we propose U-shaped Neural Operator (U-NO), a U-shaped memory enhanced architecture that allows for deeper neural operators. U-NOs exploit the problem structures in function predictions and demonstrate fast training, data …

Generative And Pseudo-Relevant Feedback For Sparse, Dense And Learned Sparse Retrieval, Iain Mackie, Shubham Chatterjee, Jeffrey Dalton

Computer Science Faculty Research & Creative Works

Pseudo-relevance feedback (PRF) is a classical approach to address lexical mismatch by enriching the query using first-pass retrieval. Moreover, recent work on generative-relevance feedback (GRF) shows that query expansion models using text generated from large language models can improve sparse retrieval without depending on first-pass retrieval effectiveness. This work extends GRF to dense and learned sparse retrieval paradigms with experiments over six standard document ranking benchmarks. We find that GRF improves over comparable PRF techniques by around 10% on both precision and recall-oriented measures. Nonetheless, query analysis shows that GRF and PRF have contrasting benefits, with GRF providing external context …

Synthesis, Characterization And Spectroscopic Studies Of Novel Donor-Acceptor Complexes, Shiyue Gao

Chemistry and Chemical Biology ETDs

Square-planar compounds of the (dichalcogenolene)Pt(diimine) series are possess unique photophysical properties that include long-lived excited state lifetimes, which result in their being potential candidates for numerous applications. These applications include solar energy conversion, photocatalysis, nonlinear optics, and photoluminescent probes of biological systems. The most interesting feature of the (dichalcogenolene)Pt(diimine) series of molecules is the bpydichalcogenolene ligand-to-ligand charge transfer (LL’CT) band. To better understand their photoluminescent decay mechanism, and understand their excited dark state properties, we have synthesized and characterized new compounds that include (Thp-bpy)Pt(CAT), (Thp2-bpy)Pt(CAT), (Thp-bpy)Pt(bdt), and (Thp2-bpy)Pt(bdt). Through interpretation of electronic absorption, resonance Raman, XAS, photoluminesce spectroscopy, in addition …

Automatic Identification Of Jetting Behavior In 3d Printing With Binary Classification And Anomaly Detection, Alexander Chandy

Honors Scholar Theses

Consistently jetting different materials from the print head of a 3D printer is a key, yet challenging task in manufacturing processes. By using active machine learning, we can efficiently predict complex diagrams that illustrate the region of printing conditions under which “desirable jetting”, “jetting”, and “no jetting” of ink occurs for different substances. However, labeling the images of printed ink droplets that are fed to the active learning model can be time intensive. Therefore, it is ideal to use computer vision to automate the classification of this image data. This classification can be broken down into two steps. In the …

Dynamic Resource Optimization For Energy-Efficient 6g-Iot Ecosystems, James Adu Ansere, Mohsin Kamal, Izaz Ahmad Khan, Muhammad Naveed Aman

School of Computing: Faculty Publications

The problem of energy optimization for Internet of Things (IoT) devices is crucial for two reasons. Firstly, IoT devices powered by renewable energy sources have limited energy resources. Secondly, the aggregate energy requirement for these small and low-powered devices is translated into significant energy consumption. Existing works show that a significant portion of an IoT device’s energy is consumed by the radio sub-system. With the emerging sixth generation (6G), energy efficiency is a major design criterion for significantly increasing the IoT network’s performance. To solve this issue, this paper focuses on maximizing the energy efficiency of the radio sub-system. In …

Halide Substitution Of Ternary Bismuth Chalcogenides For Photovoltaic Applications, Thomas Boggess

Theses and Dissertations

Semiconductors play an integral part in modern society. From computing to LEDs their use is ubiquitous, and no field is more reliant on them than that of power generation. Current political movements have seen a push to decrease reliance on traditional forms of power generation, which relies on fossil fuels, to renewable sources such as solar power. However, current commercial solar panels, based on silicon, are lacking in efficiency, only reaching between 18% and 22% efficiency.¹ In recent years, materials called perovskites have been garnering significant attention as possible replacements for silicon cells due to their favorable optoelectronic properties. …

Monolithic Multiphysics Simulation Of Hypersonic Aerothermoelasticity Using A Hybridized Discontinuous Galerkin Method, William Paul England

Theses and Dissertations

This work presents implementation of a hybridized discontinuous Galerkin (DG) method for robust simulation of the hypersonic aerothermoelastic multiphysics system. Simulation of hypersonic vehicles requires accurate resolution of complex multiphysics interactions including the effects of high-speed turbulent flow, extreme heating, and vehicle deformation due to considerable pressure loads and thermal stresses. However, the state-of-the-art procedures for hypersonic aerothermoelasticity are comprised of low-fidelity approaches and partitioned coupling schemes. These approaches preclude robust design and analysis of hypersonic vehicles for a number of reasons. First, low-fidelity approaches limit their application to simple geometries and lack the ability to capture small scale flow …

Beyond Algorithms: A User-Centered Evaluation Of A Feature Recommender System In Requirements Engineering, Oluwatobi Lasisi

Theses and Dissertations

Several studies have applied recommender technologies to support requirements engineering activities. As in other application areas of recommender systems (RS), many studies have focused on the algorithms’ prediction accuracy, while there have been limited discussions around users’ interactions with the systems. Since recommender systems are designed to aid users in information retrieval, they should be assessed not just as recommendation algorithms but also from the users’ perspective. In contrast to accuracy measures, user-related issues can only be effectively investigated via empirical studies involving real users. Furthermore, researchers are becoming increasingly aware that the effectiveness of the systems goes beyond recommendation …

Secure And Efficient Federated Learning, Xingyu Li

Theses and Dissertations

In the past 10 years, the growth of machine learning technology has been significant, largely due to the availability of large datasets for training. However, gathering a sufficient amount of data on a central server can be challenging. Additionally, with the rise of mobile networking and the large amounts of data generated by IoT devices, privacy and security issues have become a concern, resulting in government regulations such as GDPR, HIPAA, CCPA, and ADPPA. Under these circumstances, traditional centralized machine learning methods face a problem in that sensitive data must be kept locally for privacy reasons, making it difficult to …

Protecting The Vulnerable: Tornado Sheltering And Communication Of Public Shelters With A Case Study From The Covid-19 Pandemic, Craig Douglas Croskery

Theses and Dissertations

One of the greatest natural hazards that is faced with in much of the United States are tornadoes. Despite improvements in the warning processes, the risk of significant loss of life remains high. That is particularly true with vulnerable communities which have higher proportions of mobile homes; however, violent tornadoes are very difficult to manage in permanent homes or buildings as well. As a result, tornado shelters have been built in some communities and have become available to the public. However, their presence is intermittent, and there are many tornado-prone areas that lack such shelters.

After a public survey, it …

Verification Of The Localized Aviation Mos Program (Lamp) At Major Us Airports For Ifr Conditions, Mackenzie O'Rourke

Theses and Dissertations

The objective of this research is to quantify the LAMP’s performance when forecasting for IFR conditions at specific major airports for forecast hours one, three, six, and twelve, and further determine how the LAMP performs seasonally at those specific airports and forecast hours. Two by two contingency tables were used to calculate the Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), Heidke Skill Score (HSS), and Bias score. The results show that the LAMP performs relatively better in the cool season compared to the warm season consistently at each chosen airport, and that the LAMP performs …

Pairing And Rotation-Induced Nuclear Exotica In Covariant Density Functional Theory, Saja Teeti

Theses and Dissertations

Covariant density functional theory (CDFT) is one of the modern theoretical tools for describing the nuclear structure physics of finite nuclei. Its performance is defined by underlying covariant energy density functionals (CEDFs). In this dissertation and within the framework of the CDFT, different physical properties of the ground and the excited states of rotating and non-rotating nuclei have been investigated.

A systematic global investigation of pairing properties based on all available experimental data on pairing indicators has been performed for the first time in the framework of covariant density functional theory. It is based on separable pairing interaction of Ref.\ …

Eddy Current Defect Response Analysis Using Sum Of Gaussian Methods, James William Earnest

Theses and Dissertations

This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics.

Oxidation Resistance Of An Atomically Flat Cu(111) Surface: A First-Principles Study, Bipin Lamichhane

Theses and Dissertations

The first-principles calculation based on density functional theory (DFT) was used to study the oxidation resistance of atomically flat and atomic-step edges of Cu(111), diffusion of Cu atoms in different surfaces of alumina and interface properties of alumina and Cu(111), and magnetic properties of Mn-substituted strontium hexaferrite. The dissociation of oxygen molecules is the primary reason for the corrosion of metals, which deteriorates their application. Cu(111) flat surface, mono-atomic, and multi-atomic step edges were used to study oxygen diffusion. Penetration of oxygen on a Cu(111) flat surface requires high energy, indicating oxidation resistance. Our DFT result of oxygen diffusion into …

Pruning Ghsom To Create An Explainable Intrusion Detection System, Thomas Michael Kirby

Theses and Dissertations

Intrusion Detection Systems (IDS) that provide high detection rates but are black boxes lead
to models that make predictions a security analyst cannot understand. Self-Organizing Maps
(SOMs) have been used to predict intrusion to a network, while also explaining predictions through
visualization and identifying significant features. However, they have not been able to compete with
the detection rates of black box models. Growing Hierarchical Self-Organizing Maps (GHSOMs)
have been used to obtain high detection rates on the NSL-KDD and CIC-IDS-2017 network traffic
datasets, but they neglect creating explanations or visualizations, which results in another black
box model.
This paper offers …

Tornado Outbreak False Alarm Probabilistic Forecasts With Machine Learning, Kirsten Reed Snodgrass

Theses and Dissertations

Tornadic outbreaks occur annually, causing fatalities and millions of dollars in damage. By improving forecasts, the public can be better equipped to act prior to an event. False alarms (FAs) can hinder the public’s ability (or willingness) to act. As such, a probabilistic FA forecasting scheme would be beneficial to improving public response to outbreaks.

Here, a machine learning approach is employed to predict FA likelihood from Storm Prediction Center (SPC) tornado outbreak forecasts. A database of hit and FA outbreak forecasts spanning 2010 – 2020 was developed using historical SPC convective outlooks and the SPC Storm Reports database. Weather …

Analysis Of Weather-Related Flight Delays At 13 United States Airports From 2004-2019 Using A Time Series And Support Vector Regression, Caroline E. Sleeper

Theses and Dissertations

This study seeks to investigate weather-related flight delay trends at 13 United States airports. Flight delay data were collected from 2004-2019 and normalized by airport operations data. Using Support Vector Regression (SVR), visual trends were identified. Further analysis was conducted by comparing all four meteorological seasons through computing 95% bootstrap confidence intervals on their means. Finally, precipitation and snowfall data were correlated with normalized delays to investigate how they are related. This study found that the season with the highest normalized delay values is heavily dependent upon location. Most airports saw a decrease in the SVR line at some point …

The Influence Of Marsh Edge And Seagrass Habitat On Summer Fish And Macroinvertebrate Recruitment To A Northern Gulf Of Mexico Coastal System, Rebecca Lea Gilpin

Theses and Dissertations

Marshes and seagrass beds have been widely recognized as important habitat for estuarine species, but less has been done on how these habitats interact and function together, thereby limiting understanding of the variability of juvenile recruitment to coastal systems. Therefore, the objective of this study was to assess the interaction between fringing marsh and adjacent seagrass for the provision of habitat for juvenile nekton. Weekly seine net and benthic seagrass core sampling from June to November 2020 determine the relationship between nekton and marsh-edge and seagrass habitat. This study shows disparate results, in terms of the effects of proximity to …

Estimating Snow Accumulation And Ablation With L-Band Interferometric Synthetic Aperture Radar (Insar), Jack Tarricone, Ryan W. Webb, Hans-Peter Marshall, Anne W. Nolin, Franz J. Meyer

Geosciences Faculty Publications and Presentations

Snow is a critical water resource for the western United States and many regions across the globe. However, our ability to accurately measure and monitor changes in snow mass from satellite remote sensing, specifically its water equivalent, remains a challenge. To confront these challenges, NASA initiated the SnowEx program, a multiyear effort to address knowledge gaps in snow remote sensing. During SnowEx 2020, the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) team acquired an L-band interferometric synthetic aperture radar (InSAR) data time series to evaluate the capabilities and limitations of repeat-pass L-band InSAR for tracking changes in snow water equivalent …

Determining The Impact Of Post-Harvest Water Management On Chironomid Abundance, Agrochemical Biomass And Potential Trophic Biomagnification, Mason Thomas

Theses and Dissertations

Agriculture has diminished shorebirds’ natural habitat in the Mississippi Alluvial Valley. Remaining natural stopover sites are supplemented with agricultural fields during the fall and winter. This study evaluates the impact of 4 different post-harvest water management strategies on shorebird food abundance and potential agrochemical biomagnification. Chironomid samples estimated abundance, biomass, and chironomid agrochemical concentration in each field. A risk assessment of agrochemical biomagnification to shorebirds was made across all treatments. Of treatments represented on all study sites, winter treatment had greatest chironomid abundance and biomass. Models indicated that days since flood initiation, start date, and temperature are significant predictors of …

Personalized Health Care In A Data-Driven Era: A Post–Covid-19 Retrospective, Arnob Zahid, Ravishankar Sharma

All Works

No abstract provided.

Celebrating Native Chemists And Encouraging More Native Talent In Stem, Lisa Villa

Staff publications

This editorial was written to accompany cover art submitted to the American Chemical Society's 2023 ACS Diversity & Inclusion Cover Art Series, and selected as the July cover for Environmental Science & Technology Letters. The artwork design features several prominent chemists who are also strong advocates for increasing the number of Native American/First Nation scientists. They recognize how cultural beliefs may often be in conflict with scientific conversations, but have been working to attract and encourage Native American talent in the STEM fields.

The published cover art is included as a supplemental file.

Optimizing Process Conditions And Characterizing Elastomeric Properties Of Immiscible Polymers For 3d Printing Applications, Matthew Long

Electronic Theses & Dissertations

Within recent years, 3D printing within the plastics and polymer industries has becoming increasingly prevalent. Also known as additive manufacturing, 3D printing enables the creation of rapid prototypes for short production runs without the need for complex tooling. This allows for runs that are shorter and lower in cost than conventional processes. Polylactic acid (PLA) is a thermoplastic that is widely used in 3D printing for its mechanical properties and low cost. The qualities of PLA however are lacking in the areas of flexibility and toughness which is required in many prototyping scenarios. The solution to this is to incorporate …

Decoding The Flavor Of Kentucky's Native Pawpaw Fruit, Mackenzie Leanne Roark

Online Theses and Dissertations

The objective of this research was to decode the flavor of Asimina triloba, or the pawpaw fruit, to identify and quantitate the aroma-active compounds that are present. Gas chromatography – olfactometry (GC-O) was applied on capillary GC columns with various means of extraction. The volatile compounds present were extracted using both headspace solid phase micro-extraction (HS-SPME) for 30 minutes at 23°C and 50°C, and solvent extraction using methylene chloride. The sample extracts were analyzed with both gas chromatography – mass spectrometry (GC-MS) and gas chromatography – olfactometry (GC-O). To eliminate potential artifacts that were observed when using HS-SPME at 50°C, …

Feasibility Analysis Of Aeronet Lunar Aod For Nighttime Particulate Matter Estimation, Kwang Nyun Kim, Seung Hee Kim, Sang Seo Park, Yun Gon Lee

Institute for ECHO Articles and Research

Several studies have attempted to estimate particulate matter (PM) concentrations using aerosol optical depth (AOD), based on AOD and PM relationships. Owing to the limited availability of nighttime AOD data, PM estimation studies using AOD have focused on daytime. Recently, the Aerosol Robotic Network (AERONET) produced nighttime AOD, called lunar AOD, providing an opportunity to estimate nighttime PM. Nighttime AOD measurements are particularly important as they help fill gaps in our understanding of aerosol variability and its impact on the atmosphere, as there are significant variations in AOD between day and night. In this study, the relationship between lunar AOD …

Analyzing Motivation And Sense Of Belonging Belonging In Cs1 Review Sessions, Cory Longenecker

Senior Honors Projects, 2020-current

The Computer Science Department at James Madison University has a Teaching Assistant program which aims to help students succeed in early-level Computer Science courses. Part of this program is a review session, the Fourth Hour, which provides students extra help on the concepts taught each week in class. Historically, attendance at this review session has been low. Because of this, the study aimed to increase attendance by motivating students through interventions, primarily offering quiz retakes to students who attended. Additionally, this study looked at the reported sense of belonging for participants who attended.

We made three conclusions from survey data …

Exploration Of Feature Selection Techniques In Machine Learning Models On Hptlc Images For Rule Extraction, Bozidar-Brannan Kovachev

Honors Theses

Research related to Biology often utilizes machine learning models that are ultimately uninterpretable by the researcher. It would be helpful if researchers could leverage the same computing power but instead gain specific insight into decision-making to gain a deeper understanding of their domain knowledge. This paper seeks to select features and derive rules from a machine learning classification problem in biochemistry. The specific point of interest is five species of Glycyrrhiza, or Licorice, and the ability to classify them using High-Performance Thin Layer Chromatography (HPTLC) images. These images were taken using HPTLC methods under varying conditions to provide eight …

Imperfect Immunity And The Stability Of A Modified Kermack-Mckendrick Model, Kaylee Sims

Honors Theses

The classic Kermack-McKendrick model of mathematical epidemiology suggests that a population is only in equilibrium when there is no disease present. In the modern era, we have several cyclic infectious diseases that show no signs of eradication, despite global health measures. In this thesis, we introduce a coefficient of waning immunity in order to produce a modified Kermack-McKendrick model and analyze whether the model yields system stability with a certain amount of infection present. Ultimately, the model is incongruent with real-world case data, with its most glaring failure being exponential dampening of the height of each disease case peak due …