Browsing OU - Theses by Subject "Machine Learning"
Now showing items 1-20 of 33
-
Analysis of dynamics of road weather information system data
(2023-12)Road and Weather Information System consists of a network of roadside Environmental Sensor Stations (EES) collecting meteorological data. Equipped with a variety of sensors, these stations gather data including ambient ... -
Analysis of the relationships between eye tracking information and text comprehension levels in healthcare
(2017-12)Health information can be found more easily than ever through a variety of digital texts: from health forums online, informative websites, or phone apps that monitor your health. It is important that the patients are able ... -
Automated Detection of Bird Roosts Using NEXRAD Radar Data and Convolutional Neural Networks
(2017-12-15)NEXRAD radars have proven to be an effective tool for detecting bird roosts for several species or birds, however manually locating these roosts in radar images is a time consuming process. We introduce a Convolutional ... -
BIG DATA ANALYTICS IN TRANSPORTATION NETWORKS USING THE NPMRDS
(2016-05-06)Urban traffic congestion is common and the cause for loss of productivity (due to trip delays) and higher risk to passenger safety (due to increased time in the automobile), not to mention an increase in fuel consumption, ... -
Comparison of Machine Learning and Statistical Approaches for Predicting Travel Times in the Oklahoma Highway System
(2020-12)Traffic management systems play a vital role in supporting the smooth flow of traffic in road networks. By accurately predicting travel time, a traffic condition parameter that is extensively used in such systems, we can ... -
A Comparison of Machine Learning Gesture Recognition Techniques for Medication Adherence
(2020-04-27)Every year, many poor health outcomes are the result of patients missing their medication, as prescribed by their healthcare providers. Guidance and reminders to these patients would result in better health outcomes and ... -
A Constraint Driven Approach to Neural and Muscle Recruitment in Wrist Motor Tasks
(2020-07-30)The transformation from visual stimulus to muscle recruitment is a non- linear one: it must take into account the configuration of the body and the lines of action of the muscles. The primary cortex plays a role in the ... -
DATA-DRIVEN REAL-TIME GEOSTEERING USING SURFACE DRILLING DATA
(2019-12-13)In this thesis I present a method for estimating lithology or deriving formation properties from real-time surface drilling data. This information can then be used to enhance real-time geosteering capabilities. Current ... -
Deep Learning for Weak Target Detection in Range-Doppler Data
(2022-05)A consistent issue for detectors in radar systems is how to correctly distinguish target signals from random noise. This is especially true for weak targets with low signal-to-noise ratios (SNRs). Traditional target detection ... -
Development of Deep Learning Methodologies for Modeling Navigational Features in Continuous Spaces
(2021-12)This thesis proposes generalized methodologies to model navigational features of continuous spaces using deep learning architectural approaches. Navigational features impact how an entity can effectively travel within a ... -
Do We Really Need Deep Learning?: A Study on Play Identification using SEM Images
(2021-05-14)Deep learning has become an integral part of image classification and segmentation, especially with the use of convolutional neural networks (CNN) and their variants. Although computationally expensive and time-consuming, ... -
Evaluating GAM-Like Neural Network Architectures for Interpretable Machine Learning
(2019-05)In many machine learning applications, interpretability is of the utmost importance. Artificial intelligence is proliferating, but before you entrust your finances, your well-being, or even your life to a machine, you’d ... -
Forecasting landslide events in eastern Oklahoma and western Arkansas using empirical methods and statistical machine learning methods
(2022-12)Understanding the trend of landslide occurrence in eastern Oklahoma and western Arkansas is crucial to the human and social development of the region. Studies suggest rainfall is one of the major landslide triggering ... -
Gridded Hail Nowcasting using UNets, Lightning Observations, and the Warn-on-Forecast System
(2023-08-04)Hailstorms cause around 1 billion dollars in damage across the United States each year. At least a portion of this cost is associated with the inability to protect personal assets from damage in the short window of time ... -
Imbalanced Learning with Parametric Linear Programming Support Vector Machine For Weather Data Application
(2019-05-10)Learning from imbalanced data sets is one of the aspects of predictive modeling and machine learning that has taken a lot of attention in the last decade. Multiple research projects have been carried out to adjust the ... -
Investigating technologies and techniques for flood monitoring and detecting
(2022-08-04)The need for a flood alerting and forecasting system is becoming ever more critical, especially given the effects of increasing severe weather over the last ten years. Flash floods, particularly, are deadly because of the ... -
Low-Cost Video-Oculography System for Eye Tracking
(2023-05-12)The vestibular system plays a critical role in balancing and the vestibulo-ocular reflex (VOR), which aids in maintaining visual stability during head movements. Current methods of vestibular research rely on scleral coils ... -
MISSISSIPPIAN MERAMEC LITHOLOGIES AND PETROPHYSICAL PROPERTY VARIABILITY, STACK TREND, ANADARKO BASIN, OKLAHOMA
(2019-05)Mississippian Meramec reservoirs of the STACK (Sooner Trend in the Anadarko [Basin] in Canadian and Kingfisher counties) play are comprised of silty limestones, calcareous siltstones, argillaceous-calcareous siltstones, ... -
Predicting wine quality and/or taste through the use of a latent ODE-RNN Neural Net
(2019-12-13)It is common for recommendation systems to use clustering techniques for finding similar products for the downstream user. These models do not always incorporate time as a variable when recommending an item. If our ... -
Promoting Speciation Through Variable Dominance in Genetic Algorithms
(2020-05)Genetic algorithms are a class of search algorithms that have been around since the 1970s. Despite their age, genetic algorithms still see a great deal of use in various applications and so many efforts have gone into ...