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Articles 1 - 4 of 4
Full-Text Articles in Engineering
A Markov Chain Approach For Forecasting Progression Of Opioid Addiction, Abhijit Gosavi, Susan L. Murray, N. Karagiannis
A Markov Chain Approach For Forecasting Progression Of Opioid Addiction, Abhijit Gosavi, Susan L. Murray, N. Karagiannis
Engineering Management and Systems Engineering Faculty Research & Creative Works
The U.S. is currently facing an opioid crisis. Naltrexone is a common treatment for drug addiction; it reduces the desire to take opiates. However, addicts often stop treatment or continue to use opioids while in treatment. This results in increased fatalities and associated costs. A Markov-chain model is presented to analyze the progression of opioid addiction to assist the medical community in developing appropriate treatments. The model includes patients who continue opiate use while on naltrexone (blocked patients) and those who use opiates after missing naltrexone doses (unblocked patients). The other types of patients are abstinent (the best-case scenario) and …
Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli
Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
The role of human-machine teams in society is increasing, as big data and computing power explode. One popular approach to AI is deep learning, which is useful for classification, feature identification, and predictive modeling. However, deep learning models often suffer from inadequate transparency and poor explainability. One aspect of human systems integration is the design of interfaces that support human decision-making. AI models have multiple types of uncertainty embedded, which may be difficult for users to understand. Humans that use these tools need to understand how much they should trust the AI. This study evaluates one simple approach for communicating …
Framing Energy And Minerals For Future Pathways, Michelle Michot Foss, Michael S. Moats, Kwame Awuah-Offei
Framing Energy And Minerals For Future Pathways, Michelle Michot Foss, Michael S. Moats, Kwame Awuah-Offei
Materials Science and Engineering Faculty Research & Creative Works
We present a challenge for Group of Twenty (G20) discussions that entails (1) greater awareness of the role of non-fuel minerals in the global economy overall, but specifically in the energy sector; and (2) the introduction and acceleration of alternative energy sources and technologies. We focus on chemical battery energy storage, given its prominence in all views and outlooks of energy futures, especially for mobility. We present recommendations for G20 discussions and actions on battery materials, and the crucial underlying supply chains for mineral commodities.
Predictive Geohazard Mapping Using Lidar And Satellite Imagery In Missouri And Oklahoma, Usa, Olufeyisayo B. Ilesanmi
Predictive Geohazard Mapping Using Lidar And Satellite Imagery In Missouri And Oklahoma, Usa, Olufeyisayo B. Ilesanmi
Doctoral Dissertations
”Light Detection and Ranging (LiDAR) and satellite imagery have become the most utilized remote sensing technologies for compiling inventories of surficial geologic conditions. Point cloud data obtained from multi-spectral remote sensing methods provide a detailed characterization of the surface features, in particular, the detailed surface manifestations of underlying geologic structures. When combined, point clouds eliminate bias from visual inconsistencies and/or statistical values. This research explores the competence of point clouds derived from LiDAR and Unmanned Aerial Systems (UAS) as a predictive tool in evaluating various geohazards. It combines these data sets with other remote sensing techniques to evaluate the sensitivity …