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Creator | Title | Description | Subject | Date |
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Gilbert, Andrew | Computational modeling of the rat hippocampus for improving neural stimulation | Neural prostheses are used to restore some level of function to tissue damaged by disease. It is important to model and correctly identify the relationship between electrical stimulation and neural response to provide a framework for prosthetic stimulation. This work will show a struc... | Neural stimulation - Research; Hippocampus (Brain) - Research; Memory - Research; Rats as laboratory animals - Research; Neural prosthetic | 2016-05 |
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Robe, John William | The Design and Implementation of Autonomous Robotic Systems | This research focuses on the development of an autonomous robotic system using Robot Operating System (ROS), with the purpose of competing in the NASA Robotic Mining Competition in collaboration with the Utah Robotic Mining Project team. While completing this research, the following discoveries were... | | 2017 |
3 |
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Santos, Jean Paul Dytioco | Flight control systems with optimal effector allocation accounting for load constraints | This paper describes the development of quadratic optimization algorithms to be used in flight control systems; such optimization algorithms aid in distributing control efforts among available actuators to produce forces to keep aircraft stable and in flight. With the advancement of computing power,... | Flight control; Algorithms | 2013-05 |
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Luchinovich, Aleksandr | Improving measurement techniques of thin film solar cells | New, innovative solar cell technologies such as CZTS, CdTe, and hybrid perovskite solar cells are constantly being pursued in order to deliver better cost per Watt performance. Moreover, cost and long term reliability(25 years or more) are important factors that are currently considered. The Scarpu... | Solar cells - Testing; Thin films - Research; Electric power - Research; Thermal admittance spectroscopy | 2016-05 |
5 |
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Kapetanovic, Stefan | Non-Anthropomorhic Deep Learning: Developing the "Eyes for the Internet of Things" | Deep Learning (DL) and Convolutional Neural Networks (CNNs) have been established as a powerful class of models for image recognition problems. Encouraged by this, we implemented a system that can accurately predict handwritten numbers from a raw CMOS machine image. Current forms of deep learning do... | | 2017 |
6 |
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Beus, Zachary | Power system stabilizer | The goal of this project, part of the Power Industry Consortium, was to design a power system stabilizer for a small grid-connected three phase synchronous generator. Power System Stabilizers control the excitation of synchronous generators to reduce lowfrequency oscillations on the grid and increas... | Voltage regulators; Power system stabilizers | 2015-05 |
7 |
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Clark, Calli | Studying hypothetical electromagnetic earthquake precursors using a global finite-difference time-domain model | Electromagnetic (EM) precursors may be detectable by satellites and ground-based stations before large earthquakes strike and destroy entire cities. However, earthquakes are near impossible to predict as the physics of earthquake precursors is still poorly understood. This paper reports a global... | earthquake prediction - Research; Seismology - Research; Earthquake hazard analysis; Earthquake precursors; Electromagnetic signals; Ionospheric physics; Finite-difference time-domain model | 2016-04 |