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ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.


Mime Type
  • application/pdf
Date Range
2013 2019


Mobile platforms are becoming highly heterogeneous by combining a powerful multiprocessor system-on-chip (MpSoC) with numerous resources including display, memory, power management IC (PMIC), battery and wireless modems into a compact package. Furthermore, the MpSoC itself is a heterogeneous resource that integrates many processing elements such as CPU cores, GPU, video, image, and audio processors. As a result, optimization approaches targeting mobile computing needs to consider the platform at various levels of granularity. Platform energy consumption and responsiveness are two major considerations for mobile systems since they determine the battery life and user satisfaction, respectively. In this work, the models for …

Contributors
Gupta, Ujjwal, Ogras, Umit Y., Ozev, Sule, et al.
Created Date
2014

The Resistive Random Access Memory (ReRAM) is an emerging non-volatile memory technology because of its attractive attributes, including excellent scalability (< 10 nm), low programming voltage (< 3 V), fast switching speed (< 10 ns), high OFF/ON ratio (> 10), good endurance (up to 1012 cycles) and great compatibility with silicon CMOS technology [1]. However, ReRAM suffers from larger write latency, energy and reliability issue compared to Dynamic Random Access Memory (DRAM). To improve the energy-efficiency, latency efficiency and reliability of ReRAM storage systems, a low cost cross-layer approach that spans device, circuit, architecture and system levels is proposed. For …

Contributors
Mao, Manqing, Chakrabariti, Chaitali, Yu, Shimeng, et al.
Created Date
2019

Toward the ambitious long-term goal of a fleet of cooperating Flexible Autonomous Machines operating in an uncertain Environment (FAME), this thesis addresses various control objectives for ground vehicles. There are two main objectives within this thesis, first is the use of visual information to control a Differential-Drive Thunder Tumbler (DDTT) mobile robot and second is the solution to a minimum time optimal control problem for the robot around a racetrack. One method to do the first objective is by using the Position Based Visual Servoing (PBVS) approach in which a camera looks at a target and the position of the …

Contributors
Aldaco Lopez, Jesus, Rodriguez, Armando A., Artemiadis, Panagiotis K., et al.
Created Date
2016

As renewable energy becomes more prevalent in transmission and distribution systems, it is vital to understand the uncertainty and variability that accompany these resources. Microgrids have the potential to mitigate the effects of resource uncertainty. With the ability to exist in either an islanded mode or maintain connections with the main-grid, a microgrid can increase reliability, defer T&D; infrastructure and effectively utilize demand response. This study presents a co-optimization framework for a microgrid with solar photovoltaic generation, emergency generation, and transmission switching. Today unit commitment models ensure reliability with deterministic criteria, which are either insufficient to ensure reliability or can …

Contributors
Hytowitz, Robin Broder, Hedman, Kory W, Heydt, Gerald T, et al.
Created Date
2013

Coordination and control of Intelligent Agents as a team is considered in this thesis. Intelligent agents learn from experiences, and in times of uncertainty use the knowl- edge acquired to make decisions and accomplish their individual or team objectives. Agent objectives are defined using cost functions designed uniquely for the collective task being performed. Individual agent costs are coupled in such a way that group ob- jective is attained while minimizing individual costs. Information Asymmetry refers to situations where interacting agents have no knowledge or partial knowledge of cost functions of other agents. By virtue of their intelligence, i.e., by …

Contributors
KAMBAM, KARTHIK, Zhang, Wenlong, Nedich, Angelia, et al.
Created Date
2018

Increasing interest in individualized treatment strategies for prevention and treatment of health disorders has created a new application domain for dynamic modeling and control. Standard population-level clinical trials, while useful, are not the most suitable vehicle for understanding the dynamics of dosage changes to patient response. A secondary analysis of intensive longitudinal data from a naltrexone intervention for fibromyalgia examined in this dissertation shows the promise of system identification and control. This includes datacentric identification methods such as Model-on-Demand, which are attractive techniques for estimating nonlinear dynamical systems from noisy data. These methods rely on generating a local function approximation …

Contributors
Deshpande, Sunil, Rivera, Daniel E., Peet, Matthew M., et al.
Created Date
2014

Image understanding has been playing an increasingly crucial role in vision applications. Sparse models form an important component in image understanding, since the statistics of natural images reveal the presence of sparse structure. Sparse methods lead to parsimonious models, in addition to being efficient for large scale learning. In sparse modeling, data is represented as a sparse linear combination of atoms from a "dictionary" matrix. This dissertation focuses on understanding different aspects of sparse learning, thereby enhancing the use of sparse methods by incorporating tools from machine learning. With the growing need to adapt models for large scale data, it …

Contributors
Jayaraman Thiagarajan, Jayaraman, Spanias, Andreas, Frakes, David, et al.
Created Date
2013

Transmission expansion planning (TEP) is a complex decision making process that requires comprehensive analysis to determine the time, location, and number of electric power transmission facilities that are needed in the future power grid. This dissertation investigates the topic of solving TEP problems for large power systems. The dissertation can be divided into two parts. The first part of this dissertation focuses on developing a more accurate network model for TEP study. First, a mixed-integer linear programming (MILP) based TEP model is proposed for solving multi-stage TEP problems. Compared with previous work, the proposed approach reduces the number of variables …

Contributors
Zhang, Hui, Vittal, Vijay, Heydt, Gerald T, et al.
Created Date
2013

A principal goal of this dissertation is to study wireless network design and optimization with the focus on two perspectives: 1) socially-aware mobile networking and computing; 2) security and privacy in wireless networking. Under this common theme, this dissertation can be broadly organized into three parts. The first part studies socially-aware mobile networking and computing. First, it studies random access control and power control under a social group utility maximization (SGUM) framework. The socially-aware Nash equilibria (SNEs) are derived and analyzed. Then, it studies mobile crowdsensing under an incentive mechanism that exploits social trust assisted reciprocity (STAR). The efficacy of …

Contributors
Gong, Xiaowen, Zhang, Junshan, Cochran, Douglas, et al.
Created Date
2015