Physical Sciences and Mathematics Commons^™

Foundations Of Memory Capacity In Models Of Neural Cognition, Chandradeep Chowdhury

Master's Theses

A central problem in neuroscience is to understand how memories are formed as a result of the activities of neurons. Valiant’s neuroidal model attempted to address this question by modeling the brain as a random graph and memories as subgraphs within that graph. However the question of memory capacity within that model has not been explored: how many memories can the brain hold? Valiant introduced the concept of interference between memories as the defining factor for capacity; excessive interference signals the model has reached capacity. Since then, exploration of capacity has been limited, but recent investigations have delved into the …

An Empirical Evaluation Of Neural Process Meta-Learners For Financial Forecasting, Kevin G. Patel

Master's Theses

Challenges of financial forecasting, such as a dearth of independent samples and non- stationary underlying process, limit the relevance of conventional machine learning towards financial forecasting. Meta-learning approaches alleviate some of these is- sues by allowing the model to generalize across unrelated or loosely related tasks with few observations per task. The neural process family achieves this by con- ditioning forecasts based on a supplied context set at test time. Despite promise, meta-learning approaches remain underutilized in finance. To our knowledge, ours is the first application of neural processes to realized volatility (RV) forecasting and financial forecasting in general.

We …

Formal And Informal Styles Of Clothing In The Assessment Of Female Political Candidates, Erma Kurtovic

Master's Theses

Abstract: This study will research the importance of dress code of female candidates on the confidence in leadership.The research question is: How Important is the Formality of Dress Code in the Assessment of Leadership of Female Political Candidates? It is addressed by using an experimental design carried out in India and the United States, using Qualtrics and Amazon Mechanical Turk. This research gathered 400 responses, 200 from each country. Primary data collection was used, with the implementation of two experiments. The experimental design of the two experiments consisted of two conditions, one in which the main political candidate is dressed …

Modeling And Solving The Outsourcing Risk Management Problem In Multi-Echelon Supply Chains, Arian A. Nahangi

Master's Theses

Worldwide globalization has made supply chains more vulnerable to risk factors, increasing the associated costs of outsourcing goods. Outsourcing is highly beneficial for any company that values building upon its core competencies, but the emergence of the COVID-19 pandemic and other crises have exposed significant vulnerabilities within supply chains. These disruptions forced a shift in the production of goods from outsourcing to domestic methods.

This paper considers a multi-echelon supply chain model with global and domestic raw material suppliers, manufacturing plants, warehouses, and markets. All levels within the supply chain network are evaluated from a holistic perspective, calculating a total …

Node Classification On Relational Graphs Using Deep-Rgcns, Nagasai Chandra

Master's Theses

Knowledge Graphs are fascinating concepts in machine learning as they can hold usefully structured information in the form of entities and their relations. Despite the valuable applications of such graphs, most knowledge bases remain incomplete. This missing information harms downstream applications such as information retrieval and opens a window for research in statistical relational learning tasks such as node classification and link prediction. This work proposes a deep learning framework based on existing relational convolutional (R-GCN) layers to learn on highly multi-relational data characteristic of realistic knowledge graphs for node property classification tasks. We propose a deep and improved variant, …

Clustering Web Users By Mouse Movement To Detect Bots And Botnet Attacks, Justin L. Morgan

Master's Theses

The need for website administrators to efficiently and accurately detect the presence of web bots has shown to be a challenging problem. As the sophistication of modern web bots increases, specifically their ability to more closely mimic the behavior of humans, web bot detection schemes are more quickly becoming obsolete by failing to maintain effectiveness. Though machine learning-based detection schemes have been a successful approach to recent implementations, web bots are able to apply similar machine learning tactics to mimic human users, thus bypassing such detection schemes. This work seeks to address the issue of machine learning based bots bypassing …

Comparing Radiation Shielding Potential Of Liquid Propellants To Water For Application In Space, John Czaplewski

Master's Theses

The radiation environment in space is a threat that engineers and astronauts need to mitigate as exploration into the solar system expands. Passive shielding involves placing as much material between critical components and the radiation environment as possible. However, with mass and size budgets, it is important to select efficient materials to provide shielding. Currently, NASA and other space agencies plan on using water as a shield against radiation since it is already necessary for human missions. Water has been tested thoroughly and has been proven to be effective. Liquid propellants are needed for every mission and also share similar …

Incorporating Shear Resistance Into Debris Flow Triggering Model Statistics, Noah J. Lyman

Master's Theses

Several regions of the Western United States utilize statistical binary classification models to predict and manage debris flow initiation probability after wildfires. As the occurrence of wildfires and large intensity rainfall events increase, so has the frequency in which development occurs in the steep and mountainous terrain where these events arise. This resulting intersection brings with it an increasing need to derive improved results from existing models, or develop new models, to reduce the economic and human impacts that debris flows may bring. Any development or change to these models could also theoretically increase the ease of collection, processing, and …

Combining Machine Learning And Empirical Engineering Methods Towards Improving Oil Production Forecasting, Andrew J. Allen

Master's Theses

Current methods of production forecasting such as decline curve analysis (DCA) or numerical simulation require years of historical production data, and their accuracy is limited by the choice of model parameters. Unconventional resources have proven challenging to apply traditional methods of production forecasting because they lack long production histories and have extremely variable model parameters. This research proposes a data-driven alternative to reservoir simulation and production forecasting techniques. We create a proxy-well model for predicting cumulative oil production by selecting statistically significant well completion parameters and reservoir information as independent predictor variables in regression-based models. Then, principal component analysis (PCA) …

An Analysis Of Dredge Efficiency For Surfclam And Ocean Quahog Commercial Dredges, Leanne Poussard

Master's Theses

Between 1997 and 2011, The National Marine Fisheries Service conducted 50 depletion experiments to estimate survey gear efficiency and stock density for Atlantic surfclam (Spisula solidissima) and ocean quahog (Arctica islandica) populations using commercial hydraulic dredges. The Patch Model was formulated to estimate gear efficiency and organism density from the data. The range of efficiencies estimated is substantial, leading to uncertainty in the application of these estimates in stock assessment. Analysis of depletion experiment simulations showed that uncertainty in the estimates of gear efficiency from depletion experiments was reduced by higher numbers of dredge tows per experiment, more tow overlap …

An Assessment Of Convergence In The Feeding Morphology Of Xiphactinus Audax And Megalops Atlanticus Using Landmark-Based Geometric Morphometrics, Edward Chase Shelburne

Master's Theses

Convergence is an evolutionary phenomenon wherein distantly related organisms independently develop features or functional adaptations to overcome similar environmental constraints. Historically, convergence among organisms has been speculated or asserted with little rigorous or quantitative investigation. More recent advancements in systematics has allowed for the detection and study of convergence in a phylogenetic context, but this does little to elucidate convergent anatomical features in extinct taxa with poorly understood evolutionary histories. The purpose of this study is to investigate one potentially convergent system—the feeding structure of Xiphactinus audax (Teleostei: Ichthyodectiformes) and Megalops atlanticus (Teleostei: Elopiformes)—using a comparative anatomical approach to assess …

The Martingale Approach To Financial Mathematics, Jordan M. Rowley

Master's Theses

In this thesis, we will develop the fundamental properties of financial mathematics, with a focus on establishing meaningful connections between martingale theory, stochastic calculus, and measure-theoretic probability. We first consider a simple binomial model in discrete time, and assume the impossibility of earning a riskless profit, known as arbitrage. Under this no-arbitrage assumption alone, we stumble upon a strange new probability measure Q, according to which every risky asset is expected to grow as though it were a bond. As it turns out, this measure Q also gives the arbitrage-free pricing formula for every asset on our market. In …

Implementation Of Multivariate Artificial Neural Networks Coupled With Genetic Algorithms For The Multi-Objective Property Prediction And Optimization Of Emulsion Polymers, David Chisholm

Master's Theses

Machine learning has been gaining popularity over the past few decades as computers have become more advanced. On a fundamental level, machine learning consists of the use of computerized statistical methods to analyze data and discover trends that may not have been obvious or otherwise observable previously. These trends can then be used to make predictions on new data and explore entirely new design spaces. Methods vary from simple linear regression to highly complex neural networks, but the end goal is similar. The application of these methods to material property prediction and new material discovery has been of high interest …

The Long-Run Effects Of Tropical Cyclones On Infant Mortality, Isabel Miranda

Master's Theses

In the United States alone, each tropical cyclone causes an average of $14.6 billion worth of damages. In addition to the destruction of physical infrastructure, natural disasters also negatively impact human capital formation. These losses are often more difficult to observe, and therefore, are over looked when quantifying the true costs of natural disasters. One particular effect is an increase in infant mortality rates, an important indicator of a country’s general socioeconomic level. This paper utilizes a model created by Anttila-Hughes and Hsiang, that takes advantage of annual variation in tropical cyclones using annual spatial average maximum wind speeds and …

The Effect Of Vegetative Structure On Nest-Burrow Selection By The Western Burrowing Owl: Comparing Traditional Methods To Photogrammetry With An Unmanned Aerial System, Dylan J. Steffen

Master's Theses

The shortgrass prairie ecoregion in the United States has been reduced to 52% of its historical extent, contributing to reduced habitat for native species. One such species is the Burrowing Owl (Athene cunicularia). The Western Burrowing Owl subspecies (A. c. hypugaea) is listed as a Species of Special Concern in nearly every western and midwestern state, including Kansas where it is designated as a Tier II Species of Greatest Conservation Need. Habitat destruction due to conversion to cropland, increasing use of pesticides, and reduction in burrowing mammal abundance are the primary threats that have led to …

Coastal Wetland Dynamics Under Sea-Level Rise And Wetland Restoration In The Northern Gulf Of Mexico Using Bayesian Multilevel Models And A Web Tool, Tyler Hardy

Master's Theses

There is currently a lack of modeling framework to predict how relative sea-level rise (SLR), combined with restoration activities, affects landscapes of coastal wetlands with uncertainties accounted for at the entire northern Gulf of Mexico (NGOM). I developed such a modeling framework – Bayesian multi-level models to study the spatial pattern of wetland loss in the NGOM, driven by relative RSLR, vegetation productivity, tidal range, coastal slope, and wave height – all interacting with river-borne sediment availability, indicated by hydrological regimes. These interactions have not been comprehensively investigated before. I further modified this model to assess the efficacy of restoration …

The Relationship Between Stryd Power And Running Economy In Well-Trained Distance Runners 2018, Casey Austin

Master's Theses

A novel running wearable called the Stryd Summit footpod attaches to a runner’s right or left shoe and measures running power output. The developers of the product purport that the footpod’s power and form power measures may correlate with metabolic data gathered in a lab. PURPOSE: Explore the relationship between power output and running economy at threshold pace. METHODS: Seventeen well-trained distance runners, 9 males and 8 females, completed a running protocol at threshold pace. Participants ran two discontinuous four-minute stages: one with their self-selected cadence (SS), and one with cadence lowered by 10% (LC). Metabolic data, power, and form …

Life-History Characteristics And Fishery Dynamics Of Red Drum (Sciaenops Ocellatus), In The North-Central Gulf Of Mexico, Corbin Bennetts

Master's Theses

Red Drum (Sciaenops ocellatus) are highly targeted recreationally in the Gulf of Mexico, and support a small commercial fishery in Mississippi. Despite their popularity, the stock is assessed using data limited approaches that necessitate accurate life history information. I estimated the year-specific and year-aggregated escapement rates for the Mississippi stock (years 2004 to 2015), which were sensitive to mortality estimation methods; year-aggregated estimates were 6.9 to 28.2 % depending on the method, but temporal patterns were consistent. I then addressed concerns with previously estimated life-history characteristics by describing the sex-specific growth and reproductive dynamics. The three-parameter von Bertalanffy …

Reassessment Of The Red Drum Stock In Mississippi Coastal Waters: The Role Of Ages 3-5 Year-Class Fish, Emily Satterfield

Master's Theses

Red Drum, Sciaenops ocellatus, are highly sought after by sport fishermen in Mississippi coastal waters. In 2016, Mississippi anglers made over 180,000 fishing trips targeting Red Drum, making it the second most targeted marine species. The current Fishery Management Plan of the Gulf of Mexico Fishery Management Council, prohibits harvest of Red Drum in federal waters. Monitoring of the stock in Mississippi state waters occurs at sites that are almost exclusively estuarine, using gear types selective for juvenile fish. Additional samples come from the for-hire-industry that typically targets larger Red Drum. This project’s goal was to target age three …

Environmentally-Driven Variation In The Population Dynamics Of Gulf Menhaden (Brevoortia Patronus), Grant D. Adams

Master's Theses

Gulf Menhaden (Brevoortia patronus) is an abundant forage fish distributed throughout the Northern Gulf of Mexico (NGOM). Gulf Menhaden support the second largest fishery, by weight, in the United States and represent a key linkage between upper and lower trophic levels. Variation in the population dynamics can, therefore, pose consequences for the ecology and economy in the NGOM. Here we aim to understand variation in the individual and population dynamics of Gulf Menhaden throughout ontogeny and how such variation relates to environmental processes. We utilized a suite of fishery-dependent and –independent, remote sensing, modeled, and in situ data …

The Acquisition And Analysis Of Electroencephalogram Data For The Classification Of Benign Partial Epilepsy Of Childhood With Centrotemporal Spikes, Jessica A. Scarborough

Master's Theses

In this thesis, I will expand upon each step in the process of acquiring and analyzing electroencephalogram (EEG) for the classification of benign childhood epilepsy with centrotemporal spikes. Despite huge advancements in the field of health informatics—natural language processing, machine learning, predictive modeling—there are significant barriers to the access of clinical data. These barriers include information blocking, privacy policy concerns, and a lack of stakeholder support. We will see that these roadblocks are all responsible for stunting biomedical research in some way, including my own experiences in acquiring the data for the second chapter of this thesis.

This second chapter …

Effects Of Ankle Weights On Metabolic Response And Muscle Activity On A Lower Body Positive Pressure Treadmill 2017, Saige Hupman

Master's Theses

Lower body positive pressure (LBPP) treadmills are growing in popularity for rehabilitative use, as the benefits of exercising at partially supported body weight may induce faster recovery. It is unknown if there are certain practices that increase exercise intensity while maintaining positive effects of LBPP. Adding ankle weights when walking or running could increase intensity of rehabilitation programs while maintaining the comfort of supported body weight. PURPOSE: To measure metabolic response (VO2, RER, HR, Caloric expenditure), RPE, and lower limb electromyography (EMG) amplitudes of LBPP treadmill walking and running with and without ankle weights. METHODS: Sixteen participants (Age: 21.94 ± …

A Statistical Model For The Prediction Of Dissolved Oxygen Dynamics And The Potential For Hypoxia In The Mississippi Sound And Bight, Andreas Moshogianis

Master's Theses

Hypoxia events occur when dissolved oxygen concentrations fall below the minimum threshold (dissolved oxygen concentrations < 2 mg O₂ L^-1) necessary to avoid respiratory distress among aquatic organisms. In the Mississippi Sound and Bight, hypoxia is most prevalent from late-spring through late summer. Since hypoxia events can have dramatic effects on coastal fisheries, the spatial and temporal magnitude of hypoxia presents a clear threat to the productive fisheries in the northern Gulf of Mexico. Long-term hydrographic data were collected from eight sampling stations on a monthly basis from January 2009 to December 2011 along a cross-shelf transect from the mouth of …

Geographical Analysis Of Hub City Transit, Joshua Adam Watts

Master's Theses

This study assess Hub City Transit, the public bus system of Hattiesburg, MS. Statistical analysis is used to determine how well the transit system serves low income areas of the city. A 0.5 mile buffer was applied to the bus routes to determine the coverage of the transit system. Areas of disorder along the routes were also assessed to analyze the landscape routes pass through. Lastly, an analysis of ridership on each route was performed to determine the most heavily used areas, as well as to assess where riders are going on each route.

The findings show that Hub City …

Ranking Interesting Changes In Correlation Coefficient Matrix Results From Varying Data Partitions In Causal Graphic Modeling, Yesica Daniela Bravo Gonzalez

Master's Theses

Problem

In life we need to compare situations in order to select the best solution. The study in this paper is about analyzing data (variables), which is also called data mining. There are situations where it is not enough to compare variables among themselves at one specific moment. Sometimes it is necessary to compare the behavior of variables at different periods of time and know how they behave at different times in order to select the best arrangements for any situation.

Method

To find correlation among variables, traffic intersections were simulated so they could be compared, since the correlation coefficient …

A Vegetation Analysis On Horn Island, Mississippi, Ca. 1940 Using Characteristic Dimensions Derived From Historical Aerial Photography, Guy Wilburn Jeter Jr.

Master's Theses

Horn Island is part of the MS/AL barrier island chain in the northern Gulf of Mexico located approximately 18kn off the coast of Mississippi. This island’s habitats have undergone many transitions over the last several decades. The goal of this study was to quantify habitat change over a seventy year period using historical black and white photography from 1940. Using present NAIP imagery from the USDA, habitat structure was estimated by using geo-statistics, and second order statistics, from a co-occurrence matrix, to characterize texture for habitat classification. Percent land cover was then calculated to determine overall land cover change over …

Asymptotic Behavior Of Finite-Time Ruin Probability In A By-Claim Risk Model With Constant Interest Rate, Lei Wang

Master's Theses

Enlightened by the results of Li [8] and Wang [19], we study the ruin probability of a renewal risk model with constant interest rate and by-claim parts. We assume that the claim size and the inter-arrival time satisfy a certain dependent structure with some additional assumptions on their distribution functions. Furthermore, we give relevant preparation of theory and compare several existing risk models and dependent structures. In this way, we present our result and prove it.

A Proof Of Concept For Crowdsourcing Color Perception Experiments, Ryan Nathaniel Mcleod

Master's Theses

Accurately quantifying the human perception of color is an unsolved prob- lem. There are dozens of numerical systems for quantifying colors and how we as humans perceive them, but as a whole, they are far from perfect. The ability to accurately measure color for reproduction and verification is critical to indus- tries that work with textiles, paints, food and beverages, displays, and media compression algorithms. Because the science of color deals with the body, mind, and the subjective study of perception, building models of color requires largely empirical data over pure analytical science. Much of this data is extremely dated, …

An Economic Analysis Of Wine Grape Production In The State Of Connecticut, Jeremy L. Jelliffe

Master's Theses

The Connecticut Wine and Vineyard industry has grown at a steady 3.9% per year over the past decade (ATTTB, 2009). Economic models estimate that the wineries sub-sector contributes $38 million dollars to the state economy and direct employment of 106 residents (Lopez et al., 2010). Programs to support and foster further growth of the industry and CT farm vineyard culture include the Department of Agriculture’s CT Wine Trail and the annual CT Wine festival (DOAG, 2010). Farmland preservation groups also support vineyard development since grape growing tends to secure tracts of farmland for long periods of time.

Investment analysis for …

Investigation Of Trends And Predictive Effectiveness Of Crash Severity Models, James E. Mooradian

Master's Theses

This thesis describes analysis using ordinal logistic regression to uncover temporal patterns in the severity level (fatal, serious injury, minor injury, slight injury or no injury) for persons involved in highway crashes in Connecticut, focusing on the demographic split between senior travelers (65 years and over) and non-senior travelers. Existing state sources provide data describing the time and weather conditions for each crash and the vehicles and persons involved over the time period from 1995 to 2009 as well as the traffic volumes and the characteristics of the roads on which these crashes occurred. Findings indicate an overall increase in …