Physical Sciences and Mathematics Commons^™

A Predictive Flood Model For Urban Karst Groundwater Systems, Trayson Lawler

Masters Theses & Specialist Projects

Urban karst environments are often plagued by groundwater flooding, which occurs when water rises from the subsurface to the surface through the underlying caves and other karst features. The heterogeneity and interconnectedness of karst systems often makes them very unpredictable, especially during intense storm events; urbanization exacerbates the problem with the addition of many impervious surfaces. Residents in such areas are frequently disturbed and financially burdened by the effects of karst groundwater flooding. The Federal Emergency Management Agency (FEMA) offers limited protection to citizens living near flood-prone areas as they primarily focus on the areas near surface bodies of water. …

Reinforcement Learning With Deep Q-Networks, Caleb Cassady

Masters Theses & Specialist Projects

In the past decade, machine learning strategies centered on the use of Deep Neural Networks (DNNs) have caught the interest of researchers due to their success in complicated classification and prediction problems. More recently, these DNNs have been applied to reinforcement learning tasks with state of- the-art results using Deep Q-Networks (DQNs) based on the Q-Learning algorithm. However, the DQN training process is different from standard DNNs and poses significant challenges for certain reinforcement learning environments. This paper examines some of these challenges, compares proposed solutions, and offers novel solutions based on previous research. Experiment implementation available at https://github.com/caleb98/dqlearning.

Distributed Approach For Peptide Identification, Naga V K Abhinav Vedanbhatla

Masters Theses & Specialist Projects

A crucial step in protein identification is peptide identification. The Peptide Spectrum Match (PSM) information set is enormous. Hence, it is a time-consuming procedure to work on a single machine. PSMs are situated by a cross connection, a factual score, or a probability that the match between the trial and speculative is right and original. This procedure takes quite a while to execute. So, there is demand for enhancement of the performance to handle extensive peptide information sets. Development of appropriate distributed frameworks are expected to lessen the processing time.

The designed framework uses a peptide handling algorithm named C-Ranker, …