Browsing by Subject "Machine Learning"
Now showing items 1-20 of 58
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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 ... -
Application of Artificial Neural Networks, Gradient Boosted Decision Trees, and Multilevel Logistic Models in a Supervised Learning Environment to Investigate Differences in Classification Performance when Predicting College Enrollment
(2018-05)The use of data mining algorithms for applied practice is becoming commonplace in many industries. The application of these models to the domain of educational data and practice could provide significant gains in understanding ... -
Application of deep learning to optimize computer-aided-detection and diagnosis of medical images
(2023-12-15)The field of medical imaging informatics has experienced significant advancements with the integration of artificial intelligence (AI), especially in tasks like detecting abnormalities in retinal fundus images. This ... -
Application of Machine Learning to Multiple Radar Missions and Operations
(2022-08-04)This dissertation investigated the application of Machine Learning (ML) in multiple radar missions. With the increasing computational power and data availability, machine learning is becoming a convenient tool in developing ... -
Assessing the Relation between Mud Components and Rheology for Loss Circulation Prevention Using Polymeric Gels: A Machine Learning Approach
(2021-03-03)The traditional way to mitigate loss circulation in drilling operations is to use preventative and curative materials. However, it is difficult to quantify the amount of materials from every possible combination to produce ... -
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 ... -
The Context-Aware Learning Model
(2017-12)The ultimate goal of this research is to build a novel, generalized, arbitrary-depth, neural controller that performs reward- and experience-based neuromodulatory learning, which is online, bootstrapping, interactive, ... -
Coupling Data Science Techniques and Numerical Weather Prediction Models for High-Impact Weather Prediction
(2016-08-12)Meteorologists have access to more model guidance and observations than ever before, but this additional information does not necessarily lead to better forecasts. New tools are needed to reduce the cognitive load on ... -
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 ... -
Developing Novel Computer Aided Diagnosis Schemes for Improved Classification of Mammography Detected Masses
(2023-12-15)Mammography imaging is a population-based breast cancer screening tool that has greatly aided in the decrease in breast cancer mortality over time. Although mammography is the most frequently employed breast imaging modality, ... -
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 ...