Browsing by Subject "machine learning"
Now showing items 1-20 of 54
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Analysis of time series forecasting in application to solar energy harvest
(2022-05)The promised future applications in solar energy harvest have been remarkably recognized. However, the hourly forecasting of normal solar irradiance (NSI) outputs is considered a problem due to the dynamic nature of ... -
Analyzing Optimal Performance of Evolutionary Search with Restart as Problem Complexity Changes
(Oklahoma State University, 2006-12-01)This research explores how the complexity of a problem domain affects the performance of an evolutionary search using a performance-based restart policy. Previous research indicates that using a restart policy to avoid ... -
Application of Raman and infrared microscopy coupled with chemometrics for the forensic examination of automotive clear coats and paint smears
(2022-07)Modern automotive paints typically use thinner undercoat and color coat layers protected by a thicker clear coat layer. All too often, a clear coat is the only layer of automotive paint left at the crime scene. Current ... -
Application of seismic attributes and unsupervised machine learning methods for identification of hidden faults in basement and carbonate rocks
(2023-12-15)Seismic fault interpretation is a critical task for any type of energy industry and correct fault mapping can be crucial for the success of a project. Common geometric seismic attributes such as coherence and curvature are ... -
APPLICATIONS OF MACHINE LEARNING METHODS IN THE GENERATION OF SUBSURFACE MEASUREMENTS
(2018-05-11)Machine learning methods have been used in the Oil and Gas industry for about thirty years. Applications range from interpretations of geophysical, well and seismic responses, identification of minerals, analysis of rock ... -
Applied High-Order Singular Value Decomposition for Weight Compression and Expansion in Deep Neural Networks
(2019-08)Complex deep learning objectives such as object detection and saliency, semantic segmentation, sequence-to-sequence translation, and others have given rise to training processes requiring increasing amounts of time and ... -
Carbon-Based Pollutant Analysis and Remote Sensor Validation Using Column-Observing Fourier Transform Infrared (FTIR) Spectrometers During the TRACER Campaign
(2023-08-04)Greenhouse gases methane (CH4), and carbon dioxide (CO2), along with carbon monoxide (CO), while produced by both anthropogenic and natural sources, all contribute to atmospheric warming. Additionally, CO poses health risks ... -
Characterizing political ideology of tweets: Using external surrogates and few-shot learning
(Oklahoma State University, 2022-07-25) -
Comprehensive study of mobility related function in clinical notes
(Oklahoma State University, 2020-04-17)Use of free text in Electronic Health Records (EHRs) for clinical, administrative, and research purposes has proliferated in recent years. Using the Mobility domain of the ICF as a framework, we comprehensively analyze the ... -
Context-aware quality assessment of structured and unstructured data
(2020-07)Data analysis is a crucial process in the field of data science that extracts useful information from any form of data. The ease of access and maintenance makes structured data the most popular choice among many organizations ... -
Correcting, Improving, and Verifying Automated Guidance in a New Warning Paradigm
(2018-05-11)The prototype Probabilistic Hazards Information (PHI) system allows forecasters to experimentally issue dynamically evolving severe weather warning and advisory products in a testbed environment, providing hypothetical end ... -
Critical assessment of CEO succession on organizational performance through descriptive and predictive research methods
(2021-07)This research offers a comprehensive analysis of extant CEO succession literature to discover and illuminate previously unanalyzed variable relationships and potential areas for future research. An analysis is performed ... -
A Data-Driven Approach For Monitoring And Predictive Diagnosis Of Sucker Rod Pump System
(2022)Given its long operational history, a sucker-rod pump (SRP) has been widely utilized as a lifting solution to bring reservoir fluids to the surface with low cost and high efficiency. However, debugging the rod pump issues ... -
Data-driven modeling and analysis for cardiovascular disease risk prediction and reduction
(2021-05)In recent decades, cardiovascular disease (CVD) has become the leading cause of death in most countries of the world. Since many types of CVD could be preventable by modifying lifestyle behaviors, the objective of this ... -
Data-driven sub-grid model development for large eddy simulations of turbulence
(2019-05)Turbulence modeling remains an active area of research due to its significant impact on a diverse set of challenges such as those pertaining to the aerospace and geophysical communities. Researchers continue to search for ... -
Deep Autoencoders for Cross-Modal Retrieval
(2019-05-01)Increased accuracy and affordability of depth sensors such as Kinect has created a great depth-data source for 3D processing. Specifically, 3D model retrieval is attracting attention in the field of computer vision and ... -
Developing Clinical Decision Support Systems for Sepsis Prediction Using Temporal and Non-Temporal Machine Learning Methods
(2019-07)In healthcare, diagnostic errors represent the biggest challenge to synthesize accurate treatments. In the United States, patient deaths due to misdiagnoses are estimated at 40,000 to 80,000 per year. It was also found ... -
Digital Transformation: How to Beat the High Failure Rate
(2019-05-01)Firms every year spend $1.3 trillion on digital transformation programs to improve efficiency because digital leaders outperform their peers in nearly every industry. However, digital transformations that are intended to ... -
Energy Efficient Machine Learning-Based Classification of ECG Heartbeat Types
(2018-12-05)To meet the accuracy, latency and energy efficiency requirements during real-time collection and analysis of health data, a distributed edge computing environment is the answer, combined with 5G speeds and modern computing ... -
Examining Seismic Amplitude Responses of Gaseous Media Using Unsupervised Machine Learning
(2020-12-18)The presence of gas in the rock’s or sediment’s pore space significantly affects its seismic amplitude response and modifies its subsurface signature. Gas hydrates in the subsurface are often difficult to image with ...