Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 7 of 7
Full-Text Articles in Entire DC Network
Applying Cognitive Measures In Counterfactual Prediction, Lori A. Mahoney
Applying Cognitive Measures In Counterfactual Prediction, Lori A. Mahoney
Browse all Theses and Dissertations
Counterfactual reasoning can be used in task-switching scenarios, such as design and planning tasks, to learn from past behavior, predict future performance, and customize interventions leading to enhanced performance. Previous research has focused on external factors and personality traits; there is a lack of research exploring how the decision-making process relates to both task-switching and counterfactual predictions. The purpose of this dissertation is to describe and explain individual differences in task-switching strategy and cognitive processes using machine learning techniques and linear ballistic accumulator (LBA) models, respectively, and apply those results in counterfactual models to predict behavior. Applying machine learning techniques …
Computational Simulation And Analysis Of Neuroplasticity, Madison E. Yancey
Computational Simulation And Analysis Of Neuroplasticity, Madison E. Yancey
Browse all Theses and Dissertations
Homeostatic synaptic plasticity is the process by which neurons alter their activity in response to changes in network activity. Neuroscientists attempting to understand homeostatic synaptic plasticity have developed three different mathematical methods to analyze collections of event recordings from neurons acting as a proxy for neuronal activity. These collections of events are from control data and treatment data, referring to the treatment of neuron cultures with pharmacological agents that augment or inhibit network activity. If the distribution of control events can be functionally mapped to the distribution of treatment events, a better understanding of the biological processes underlying homeostatic synaptic …
Applying Cognitive Measures In Counterfactual Prediction, Lori A. Mahoney
Applying Cognitive Measures In Counterfactual Prediction, Lori A. Mahoney
Browse all Theses and Dissertations
Counterfactual reasoning can be used in task-switching scenarios, such as design and planning tasks, to learn from past behavior, predict future performance, and customize interventions leading to enhanced performance. Previous research has focused on external factors and personality traits; there is a lack of research exploring how the decision-making process relates to both task-switching and counterfactual predictions. The purpose of this dissertation is to describe and explain individual differences in task-switching strategy and cognitive processes using machine learning techniques and linear ballistic accumulator (LBA) models, respectively, and apply those results in counterfactual models to predict behavior. Applying machine learning techniques …
Bayesian Inspired Multi-Fidelity Optimization With Aerodynamic Design, Christopher Corey Fischer
Bayesian Inspired Multi-Fidelity Optimization With Aerodynamic Design, Christopher Corey Fischer
Browse all Theses and Dissertations
In most engineering design problems, there exist multiple models of varying fidelities for use in predicting a single system response such as Computational Fluid Dynamics (CFD) models constructed using Potential Flow, Euler equations, or full physics Navier Stokes implementation. Engineering design is constantly pushing the forefront of the field through imposing stricter and more complex constraints on system performance, thus elevating the need for use of high-fidelity models in the design process. Increasing fidelity level often correlates to an increase in cost (financial, computational time, and computational resources). Traditional design processes rely upon low-fidelity models for expedience and resource savings. …
Intersections Of Deleted Digits Cantor Sets With Gaussian Integer Bases, Vincent T. Shaw
Intersections Of Deleted Digits Cantor Sets With Gaussian Integer Bases, Vincent T. Shaw
Browse all Theses and Dissertations
In this paper, the intersections of deleted digits Cantor sets and their fractal dimensions were analyzed. Previously, it had been shown that for any dimension between 0 and the dimension of the given deleted digits Cantor set of the real number line, a translate of the set could be constructed such that the intersection of the set with the translate would have this dimension. Here, we consider deleted digits Cantor sets of the complex plane with Gaussian integer bases and show that the result still holds.
Efficient Numerical Methods For Chemotaxis And Plasma Modulation Instability Studies, Truong B. Nguyen
Efficient Numerical Methods For Chemotaxis And Plasma Modulation Instability Studies, Truong B. Nguyen
Browse all Theses and Dissertations
In this thesis, we develop efficient numerical solvers for nonlinear systems of partial differential equations (PDEs). These systems of PDEs concern two different sets of physical problems. The first set includes chemotaxis models such as Keller-Segel models and cancer cell invasion models. Solutions of these models are observed to experience the blow-up phenomenon or the development of sharp and spiky features. Therefore, efficient and accurate numerical techniques must be employed in order to capture the solutions' behaviors. For this research, we design efficient solvers for these systems in the one and two spatial dimensions. In particular, we plan to apply …
Power Distribution And Probabilistic Forecasting Of Economic Loss And Fatalities Due To Hurricanes, Earthquakes, Tornadoes, And Floods In The United States, Scott Edward Baker
Power Distribution And Probabilistic Forecasting Of Economic Loss And Fatalities Due To Hurricanes, Earthquakes, Tornadoes, And Floods In The United States, Scott Edward Baker
Browse all Theses and Dissertations
Traditionally, the size of natural disaster events such as hurricanes, earthquakes, tornadoes, and floods is measured in terms of wind speed (m/sec), energy released (ergs), or discharge (m3/sec). Economic loss and fatalities from natural disasters result from the intersection of the human infrastructure and population with the natural event. This study investigates the size versus cumulative number distribution of individual natural disaster events in the United States. Economic losses are adjusted for inflation to 2014 United States Dollars (USD). The cumulative number divided by the time over which the data ranges is the basis for making probabilistic forecasts in terms …