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Full-Text Articles in Engineering

High Order Explicit Semi-Lagrangian Method For The Solution Of Lagrangian Transport And Stochastic Differential Equations, Hareshram Natarajan Jan 2020

High Order Explicit Semi-Lagrangian Method For The Solution Of Lagrangian Transport And Stochastic Differential Equations, Hareshram Natarajan

CGU Theses & Dissertations

A semi-Lagrangian method is developed for the solution of Lagrangian transport equations and stochastic differential equations that is consistent with Discontinuous Spectral Element Method (DSEM) approximations of Eulerian conservation laws. The method extends the favorable properties of DSEM that include its high-order accuracy, its local and boundary fitted properties and its high performance on parallel platforms for the concurrent semi-Lagrangian and Eulerian solution of a class of time-dependent problems that can be described by coupled Eulerian-Lagrangian formulations. Such formulations include the probabilistic models used for the simulation of chemically reacting turbulent flows or particle-laden flows. Motivated by the high-fidelity simulation …


Analysis And Optimization Of Chassis Movements In Transportation Networks With Centralized Chassis Processing Facilities, Timothy Martin Vanderbeek Jan 2019

Analysis And Optimization Of Chassis Movements In Transportation Networks With Centralized Chassis Processing Facilities, Timothy Martin Vanderbeek

CGU Theses & Dissertations

This work studies the concept of “Centralized Processing of Chassis,” and its potential impact on port drayage efficiency. The concept revolves around an off-dock terminal (or several off-dock terminals), referred to as Chassis Processing Facilities (CPFs). A CPF is located close to the port, where trucks will go to exchange chassis, thereby reducing traffic at the marine terminals and resulting in reduced travel times and reduced congestion. This work is divided into two major studies: one at the strategic planning level, and one at the operational level for individual trucking companies.

In the first study, an analytical framework for modeling …


Prediction Of The Outcome In Cardiac Arrest Patients Undergoing Hypothermia Using Eeg Wavelet Entropy, Hana Moshirvaziri Jan 2019

Prediction Of The Outcome In Cardiac Arrest Patients Undergoing Hypothermia Using Eeg Wavelet Entropy, Hana Moshirvaziri

CGU Theses & Dissertations

Cardiac arrest (CA) is the leading cause of death in the United States. Induction of hypothermia has been found to improve the functional recovery of CA patients after resuscitation. However, there is no clear guideline for the clinicians yet to determine the prognosis of the CA when patients are treated with hypothermia. The present work aimed at the development of a prognostic marker for the CA patients undergoing hypothermia. A quantitative measure of the complexity of Electroencephalogram (EEG) signals, called wavelet sub-band entropy, was employed to predict the patients’ outcomes. We hypothesized that the EEG signals of the patients who …


One-Bit Compressive Sensing With Partial Support Information, Phillip North Jan 2015

One-Bit Compressive Sensing With Partial Support Information, Phillip North

CMC Senior Theses

This work develops novel algorithms for incorporating prior-support information into the field of One-Bit Compressed Sensing. Traditionally, Compressed Sensing is used for acquiring high-dimensional signals from few linear measurements. In applications, it is often the case that we have some knowledge of the structure of our signal(s) beforehand, and thus we would like to leverage it to attain more accurate and efficient recovery. Additionally, the Compressive Sensing framework maintains relevance even when the available measurements are subject to extreme quantization. Indeed, the field of One-Bit Compressive Sensing aims to recover a signal from measurements reduced to only their sign-bit. This …


A Mathematical Framework For Unmanned Aerial Vehicle Obstacle Avoidance, Sorathan Chaturapruek Jan 2014

A Mathematical Framework For Unmanned Aerial Vehicle Obstacle Avoidance, Sorathan Chaturapruek

HMC Senior Theses

The obstacle avoidance navigation problem for Unmanned Aerial Vehicles (UAVs) is a very challenging problem. It lies at the intersection of many fields such as probability, differential geometry, optimal control, and robotics. We build a mathematical framework to solve this problem for quadrotors using both a theoretical approach through a Hamiltonian system and a machine learning approach that learns from human sub-experts' multiple demonstrations in obstacle avoidance. Prior research on the machine learning approach uses an algorithm that does not incorporate geometry. We have developed tools to solve and test the obstacle avoidance problem through mathematics.