Browsing The University of Oklahoma by Subject "Machine Learning"
Now showing items 41-59 of 59
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Respiratory Rate Estimation Using WiFi Channel State Information - A Machine Learning Approach
(2020)Respiratory rate (RR) is an important vital sign for diagnosing and treating a number of medical conditions. Current respiration monitoring systems require that a special device is continuously attached to the human body. ... -
RWIS based road condition prediction using machine learning algorithms
(2021-06-26)The need for a forecasting model of road conditions is becoming evermore critical, given the effects of ever-increasing severity in weather. Drastic changes in weather, especially cold fronts, often lead to dangerous roads. ... -
Scaling up Labeling, Mining, and Inferencing on Event Extraction
(2022-05)Numerous important events happen every day and are reported in different media sources with varying narrative styles across different knowledge domains and languages. Detecting the real-world events that have been reported ... -
Search for third generation vector-like leptons with the ATLAS detector
(2022-03-09)The Standard Model of particle physics provides a concise description of the building blocks of our universe in terms of fundamental particles and their interactions. It is an extremely successful theory, providing a ... -
Secure Decentralized Decisions in Consolidated Hospital Systems: Intelligent Agents and Blockchain
(2018)Shared decision making has become a very important solution in order to build a consolidated healthcare system. While there is some research in the healthcare literature discussing the advantages and disadvantages of the ... -
Seismic attribute optimization with unsupervised machine learning techniques for deepwater seismic facies interpretation: users vs machines
(2020-07)Machine learning (ML) has many applications within the geosciences, from predicting seismic facies, to automatic fault detection. A variety of machine learning algorithms are commonly employed, among these principal component ... -
SEISMIC EXPRESSION OF IGNEOUS BODIES IN SEDIMENTARY BASINS AND THEIR IMPACT ON HYDROCARBON EXPLORATION: EXAMPLES FROM A COMPRESSIVE TECTONIC SETTING, TARANAKI BASIN, NEW ZEALAND
(2018-05-11)The impact of Neogene volcanism on hydrocarbon exploration in the Taranaki Basin, New Zealand remains under-explored. To better understand these effects, I performed detailed seismic interpretation coupled with examination ... -
Seismic Reprocessing of a Granite Wash Survey, Buffalow Wallow Field, Anadarko Basin, Texas
(2017-12-16)Although considered one of the more productive oil and gas reservoirs in the United States, the Pennsylvanian-age Granite Wash reservoir remain poorly understood. Amongst a myriad of issues that hinder development of ... -
A simulation and analytical study on the performance of gas-liquid centrifugal downhole separators
(2023-12-15)A common issue in depleted oil and gas wells is the lack of energy to drive the fluids to the surface. Engineers use various artificial lift systems to solve this problem, most commonly by using pumps. Many pump types do ... -
A Simulation Study Comparing the Use of Supervised Machine Learning Variable Selection Methods in the Psychological Sciences
(2022)When specifying a predictive model for classification, variable selection (or subset selection) is one of the most important steps for researchers to consider. Reducing the necessary number of variables in a prediction ... -
SINGLE CELL METABOLOMICS USING MASS SPECTROMETRY: DEVICES, METHODS AND APPLICATIONS
(2019-05-10)Cells are basic functional components of eukaryotic organisms containing rich biological and physiological information. To investigate the nature of cells, a variety of fundamental and mechanistic studies of the cell ... -
Single-probe Mass Spectrometry Imaging: Applications and Advanced Data Analysis
(2019-12)Mass spectrometry imaging (MSI) is becoming a powerful tool in the bioanalytical studies owing to its unique capability to sensitively map the spatial distribution of broad ranges of molecules on biological samples. Due ... -
Statistical and deep learning methods for geoscience problems
(2021-12-15)Machine learning is the new frontier for technology development in geosciences and has developed extremely fast in the past decade. With the increased compute power provided by distributed computing and Graphics Processing ... -
Storm-scale Ensemble-based Severe Weather Guidance: Development of an Object-based Verification Framework and Applications of Machine Learning
(2020-12-18)A goal of the National Oceanic and Atmospheric Administration (NOAA) Warn-on-Forecast (WoF) project is to provide rapidly updating probabilistic guidance to human forecasters for short-term (e.g., 0-3 h) severe weather ... -
A supervised machine learning approach to discriminate reservoir fluid presence and saturation in the Gulf of Mexico using frequency and spectral shape attributes
(2023-05-13)The first chapter in this research aims to define reliable attributes to differentiate subsurface fluids and measure their attenuation to provide insights into reservoir properties. The study investigates the effects ... -
Theory-Guided Algorithm Design for Scalable Machine Learning
(2023-05-12)My thesis focuses on designing scalable machine learning algorithms leveraging theoretical advances in mathematics. In particular, I investigate two directions where scalability plays an important role: fair machine learning ... -
Traffic accident analysis and prediction using the NPMRDS
(2020-12)Traffic accidents are incidents caused by collisions between road vehicles or a vehicle with road infrastructures or pedestrians. Traffic accidents are a common cause for non-recurring traffic bottlenecks that, in turn, ... -
Using Machine Learning to Improve the NSSL's Warn-On-Forecast System's Prediction of Thunderstorm Location
(2023-08-04)Deep learning (DL) models have become immensely popular in recent years, with many models creating accurate and high-skill predictions for a wide range of atmospheric phenomena. Using DL models for predicting convection ... -
Video Outpainting using Conditional Generative Adverarial Networks
(2021)Recent advancements in machine learning and neural networks have pushed the boundaries of what computers can achieve. Generative adversarial networks are a specific type of neural network that have proved wildly successful ...