Social and Behavioral Sciences Commons^™

Evaluating Barriers To And Impacts Of Rural Broadband Access, Javier Valentín-Sívico

Doctoral Dissertations

"The lack of adequate broadband infrastructure persists in many rural communities. Beyond funding, additional barriers persist, such as digital literacy and community-level self-efficacy. As a result, the first contribution articulates barriers at the organizational level. This work proposes a framework based on the Theory of Planned Behavior to highlight stakeholder dynamics that have constrained Regional Planning Commissions from advancing broadband infrastructure in rural areas. One approach to address these barriers is to provide stakeholders with analytical tools to evaluate the benefits and costs of various broadband options for their community since there is not a one-size-fits-all solution. To this end, …

The Implementation Of Energy Sharing Using A System Of Systems Approach, Julia Morgan

Doctoral Dissertations

"There is an increasing demand for renewable energy and consumers need more procurement options to meet their needs. Energy sharing provides a peer-to-peer (P2P) marketplace where prosumer electricity is redistributed to fellow energy-sharing community participants. This redistribution of prosumer electricity provides consumers with additional electricity suppliers, while also decreasing the load on the utility company. Though significant progress has been made regarding research and implementation of energy sharing, there is still room for growth when evaluating energy-sharing communities and defining appropriate community coordination based on end-user needs. The first contribution in this work identified nine characteristics of energy-sharing communities as …

Modeling Time Series With Conditional Heteroscedastic Structure, Ratnayake Mudiyanselage Isuru Panduka Ratnayake

Doctoral Dissertations

"Models with a conditional heteroscedastic variance structure play a vital role in many applications, including modeling financial volatility. In this dissertation several existing formulations, motivated by the Generalized Autoregressive Conditional Heteroscedastic model, are further generalized to provide more effective modeling of price range data well as count data. First, the Conditional Autoregressive Range (CARR) model is generalized by introducing a composite range-based multiplicative component formulation named the Composite CARR model. This formulation enables a more effective modeling of the long and short-term volatility components present in price range data. It treats the long-term volatility as a stochastic component that in …

Gis And Remote Sensing Groundwater Potentiality Investigation Of Gulu District, Uganda Using Synthetic Aperture Radar And Magnetic Geophysics, Rachel Ann Jones

Doctoral Dissertations

“Developing countries have few resources for ground-based hydrological investigations to determine optimal placement of boreholes for community water access. Remote sensing data are available at a variety of resolutions and sense different parameters, and are useful inputs for hydrologic models, but these data are rarely obtainable in developing countries with the parameters or resolutions necessary for hydrologic applications. This research seeks to use and improve existing remote sensing and GIS techniques to identify areas of optimal water supply in locations with limited geologic or hydrologic information, such as Gulu District, Uganda. Fusing different remotely sensed data sets can produce higher …

Infrastructure Systems Modeling Using Data Visualization And Trend Extraction, Jacob Marshal Hale

Doctoral Dissertations

“Current infrastructure systems modeling literature lacks frameworks that integrate data visualization and trend extraction needed for complex systems decision making and planning. Critical infrastructures such as transportation and energy systems contain interdependencies that cannot be properly characterized without considering data visualization and trend extraction.

This dissertation presents two case analyses to showcase the effectiveness and improvements that can be made using these techniques. Case one examines flood management and mitigation of disruption impacts using geospatial characteristics as part of data visualization. Case two incorporates trend analysis and sustainability assessment into energy portfolio transitions.

Four distinct contributions are made in this …

Predictive Geohazard Mapping Using Lidar And Satellite Imagery In Missouri And Oklahoma, Usa, Olufeyisayo B. Ilesanmi

Doctoral Dissertations

”Light Detection and Ranging (LiDAR) and satellite imagery have become the most utilized remote sensing technologies for compiling inventories of surficial geologic conditions. Point cloud data obtained from multi-spectral remote sensing methods provide a detailed characterization of the surface features, in particular, the detailed surface manifestations of underlying geologic structures. When combined, point clouds eliminate bias from visual inconsistencies and/or statistical values. This research explores the competence of point clouds derived from LiDAR and Unmanned Aerial Systems (UAS) as a predictive tool in evaluating various geohazards. It combines these data sets with other remote sensing techniques to evaluate the sensitivity …

The Behavior Of Suas Under Explosive Loading Conditions And Implications For Safe Operating Procedures, Ashok Em Sudhakar

Doctoral Dissertations

"Drones are increasingly being used for tasks previously unimagined and the beneficial uses are evolving. The United States Congress has envisioned the possible uses of drones for both combating and conveying explosive threats and other harmful and destructive activities. Congress' intent is reflected in new laws (2018) and policies (2019).

All civilian available Small Unmanned Aerial Systems sUASs (Drones), weighing less than 55 pounds, in the current market are not designed for operations in explosive environments. This first of a kind research focuses on further understanding of sUASs response to explosive loading and the public policy implications. This research measured …

Military Applications Of Geological Engineering, Stephen H. Tupper

Doctoral Dissertations

"This work examines the premise that military engineering and geological engineering are intellectually paired and overlapped in practice to a significant extent. Geological engineering is an established, albeit young, academic discipline that enjoys wide industry and civil demand and is supported by many professional organizations. In contrast, military engineering is an ancient, empirically derived training or "OJT" program with practice-based trade-associations that has narrow government-only utility. The premise is formed by decades-long observation of U. S. Army military engineer officers completing a Master of Science degree in geological engineering as a complement to their practice-based training in military engineering at …

A Systems And Cost Analysis Of Human Rated Mars Entry, Descent, And Landing Vehicles, Paul Daniel Friz

Doctoral Dissertations

"Cost is one of the biggest obstacles to sending humans to Mars. However, spacecraft costs are typically not taken into consideration until after the preliminary vehicle and mission concepts have been designed. Once costs have been estimated, managers and project teams often lack confidence that the final cost of the mission will match the preliminary estimates. The present work provides a robust methodology for using cost as a valid metric early in the design phase of future human Mars Entry, Descent, and Landing (EDL) vehicles. This is done in three parts. First, state of the art parametric costing methods are …

Cognition-Based Approaches For High-Precision Text Mining, George John Shannon

Doctoral Dissertations

"This research improves the precision of information extraction from free-form text via the use of cognitive-based approaches to natural language processing (NLP). Cognitive-based approaches are an important, and relatively new, area of research in NLP and search, as well as linguistics. Cognitive approaches enable significant improvements in both the breadth and depth of knowledge extracted from text. This research has made contributions in the areas of a cognitive approach to automated concept recognition in.

Cognitive approaches to search, also called concept-based search, have been shown to improve search precision. Given the tremendous amount of electronic text generated in our digital …

Proactive Search: Using Outcome-Based Dynamic Nearest-Neighbor Recommendation Algorithms To Improve Search Engine Efficacy, Christopher Shaun Wagner

Doctoral Dissertations

"The explosion of readily available electronic information has changed the focus of data processing from data generation to data discovery. The prevalent use of search engines has generated extensive research into improving the speed and accuracy of searches. The goal of this research is to accurately predict user behavior as a means to proactively improve speed, accuracy, and predictability of search engines. The proactive approach eliminates query entry time and hence reduces the overall processing time, improving speed. Assuming success, the user locates an electronic resource of interest, improving accuracy.

Algorithms that have been shown to predict many vastly different …