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Now showing items 11-20 of 24
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 ...
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 ...
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 ...
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 ...
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. ...
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 ...
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 ...
Using Machine Learning to Predict Damaging Straight-line Convective Winds
(2016-08-12)
Thunderstorms, including straight-line (non-tornadic) winds, cause an average of over 100 deaths and $10 billion of insured damage per year in the United States. In the past decade machine learning has led to significant ...
Woodford Shale enclosed mini-basin fill on the Hunton Paleo Shelf. A depositional model for unconventional resource shales
(2020-05-08)
The exploration of unconventional hydrocarbon resources of the Woodford Shale in Oklahoma (USA) has focused on characterizing this formation as an entirely open marine deposit. The impact of recognizing the enclosed ...