Computational Engineering Commons^™

A Deep Learning Model For Predicting Covid-19 Transmission In Connecticut, Nathan Choi

Honors Scholar Theses

COVID-19 has immensely impacted life as we know it, as the virus quickly spread throughout the entire world in a matter of weeks since its emergence. It has toppled economies, tested healthcare systems worldwide, and has un- fortunately taken the lives of many in the process. While extensive research has analyzed the issue on a large scale, focusing on entire countries and states, there has not been as much focus on the meso-scale, mainly compris- ing towns and cities, due to the lack of available COVID-19 data at this scale. However, in the case of countries like the United States …

Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah

Honors Scholar Theses

Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?

In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not communicate with …

Cooperative 3-D Map Generation Using Multiple Uavs, Andrew Erik Lawson

University Scholar Projects

This report aims to demonstrate the feasibility of building a global 3-D map from multiple UAV robots in a GPS-denied, indoor environment. Presented are the design of each robot and the reasoning behind choosing its hardware and software components, the process in which a single robot obtains a individual 3-D map entirely onboard, and lastly how the mapping concept is extended to multiple robotic agents to form a global 3-D map using a centralized server. In the latter section, this report focuses on two algorithms, Online Mapping and Map Fusion, developed to facilitate the cooperative approach. A limited selection …

Efficient Algorithms For Fast Integration On Large Data Sets From Multiple Sources, Tian Mi, Sanguthevar Rajasekaran, Robert H. Aseltine

Open Access Author Fund Awardees' Articles

Background

Recent large scale deployments of health information technology have created opportunities for the integration of patient medical records with disparate public health, human service, and educational databases to provide comprehensive information related to health and development. Data integration techniques, which identify records belonging to the same individual that reside in multiple data sets, are essential to these efforts. Several algorithms have been proposed in the literatures that are adept in integrating records from two different datasets. Our algorithms are aimed at integrating multiple (in particular more than two) datasets efficiently.

Methods

Hierarchical clustering based solutions are used to integrate …