Browsing by Subject "Machine learning"
Now showing items 1-20 of 23
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Applying novel machine learning technology to optimize computer-aided detection and diagnosis of medical images
(2021-05-14)The purpose of developing Computer-Aided Detection (CAD) schemes is to assist physicians (i.e., radiologists) in interpreting medical imaging findings and reducing inter-reader variability more accurately. In developing ... -
Assessment of spectral attributes in identifying gas hydrates in seismic data from the Pegasus Basin, offshore New Zealand
(2023-05-13)Gas hydrates are formed in the subsurface along shallow ocean basins or in permafrost settings, and are commonly identified in the seismic data by the bottom-simulating reflector (BSR). Various methods have been employed ... -
Automatic Leak Detection in Carbon Sequestration Projects
(2020-05-15)The international commitments for carbon capture will require a rapid increase in carbon capture and storage (CCS) projects. The key to any successful carbon sequestration project lies in the long term storage and ... -
Combining seismic attributes and machine learning for seismic facies analysis
(2022-05-13)Understanding how to correctly select a group of input seismic attributes is critical to perform a robust machine learning (ML)-based seismic facies analysis. However, due to the large number of seismic attributes enhancing ... -
CONNECTIVITIES OF VARIOUS COMPONENTS IN ORGANIC-RICH SHALE
(2019)The physical properties of shale are fundamentally controlled by its microstructure. Connectivity of various components in shale is an important property that governs the transport of mass, energy and momentum. Quantifying ... -
Developing and Applying CAD-generated Image Markers to Assist Disease Diagnosis and Prognosis Prediction
(2022-05-13)Developing computer-aided detection and/or diagnosis (CAD) schemes has been an active research topic in medical imaging informatics (MII) with promising results in assisting clinicians in making better diagnostic and/or ... -
Developing novel quantitative imaging analysis schemes based machine learning for cancer research
(2021-05-14)The computer-aided detection (CAD) scheme is a developing technology in the medical imaging field, and it attracted extensive research interest in recent years. In this dissertation, I investigated the feasibility of ... -
Development of polymer gel systems for lost circulation treatment and wellbore strengthening
(2021-05-07)Lost circulation is a frequent problem and a significant contributor to the non-productive time (NPT) in the drilling operation. Field reports and experimental studies have revealed that conventional solutions are doomed ... -
Enhancing Performance and Reducing Emissions in Natural Gas Aspirated Engines through Machine Learning Algorithm
(2023-12-15)In an era where the global energy landscape is increasingly defined by the dual imperatives of efficiency and sustainability, the natural gas sector stands at a crucial juncture. The engines powering this sector, especially ... -
Integrated characterization of tight siliciclastic reservoirs: examples from the Cretaceous Burro Canyon Formation, Colorado, and Mississippian Meramec Strata, Oklahoma
(2021-05-14)Integration of multiscale data sources for reservoir characterization becomes problematic and challenging due to the collected information variable resolution. Core and well data provide high vertical resolution to evaluate ... -
Investigating the potential of synthetic data for enabling AI-based zero-touch network automation
(2021)The essence and importance of rich and relevant data can not be overemphasized in the field of artificial intelligence. From machine learning to deep learning models, the performance of a model is majorly dependent on the ... -
Machine learning assisted molecular simulations / mass spectrometry data analysis and rational design of antibacterial Co3O4 nanowires flagella
(2023-05-12)In chapter one, inspired by the recent work from Noé and coworkers on the development of machine learning based implicit solvent model for the simulation of solvated peptides [Chen et al., J. Chem. Phys. 155, 084101 (2021)], ... -
Machine learning for the subsurface characterization at core, well, and reservoir scales
(2020-05-08)The development of machine learning techniques and the digitization of the subsurface geophysical/petrophysical measurements provides a new opportunity for the industries focusing on exploration and extraction of subsurface ... -
Novel Computer-Aided Diagnosis Schemes for Radiological Image Analysis
(2022-05-13)The computer-aided diagnosis (CAD) scheme is a powerful tool in assisting clinicians (e.g., radiologists) to interpret medical images more accurately and efficiently. In developing high-performing CAD schemes, classic ... -
Optimization of deepwater channel seismic reservoir characterization using seismic attributes and machine learning
(2023-12-15)Accurate subsurface reservoir mapping is essential for resource exploration. In uncalibrated basins, seismic data, often limited by resolution, frequency, quality, etc., algorithms become the primary information source due ... -
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. ... -
Stratigraphic and diagenetic controls on petrofacies and reservoir-quality variability using semi-supervised and supervised machine learning methods: Sycamore Formation, Sho-Vel-Tum Field, Oklahoma, USA
(2021-12-18)Diagenetic processes in sedimentary rocks have intrigued geologists, but they are poorly understood. In sedimentary fine-grained rocks, there is even less information, due to the complexity and lack of interest despite the ... -
SUB-SEISMIC REEF CHARACTERIZATION USING MACHINE LEARNING AND MULTI-ATTRIBUTE ANALYSIS
(2020)Historically, Silurian reef complexes in the Michigan Basin have been largely identified using 2D seismic surveys with very little research focusing on characterizing these reefs (morphology, internal architecture, reservoir ... -
TOWARD ENHANCED WIRELESS COEXISTENCE IN THE 2.4GHZ ISM BAND VIA TEMPORAL CHARACTERIZATION AND EMPIRICAL MODELING OF 802.11B/G/N NETWORKS A DISSERTATION
(2016)This dissertation presents an extensive experimental characterization and empirical modelling of 802.11 temporal behavior. A detailed characterization of 802.11b/g/n homogeneous and heterogeneous network traffic patterns ... -
Unconstrained Learning Machines
(2010)With the use of information technology in industries, a new need has arisen in analyzing large scale data sets and automating data analysis that was once performed by human intuition and simple analog processing machines. ...