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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.


Contributor
Subject
Date Range
2011 2020


Object detection is an interesting computer vision area that is concerned with the detection of object instances belonging to specific classes of interest as well as the localization of these instances in images and/or videos. Object detection serves as a vital module in many computer vision based applications. This work focuses on the development of object detection methods that exhibit increased robustness to varying illuminations and image quality. In this work, two methods for robust object detection are presented. In the context of varying illumination, this work focuses on robust generic obstacle detection and collision warning in Advanced Driver Assistance …

Contributors
PRAKASH, CHARAN DUDDA, Karam, Lina, Abousleman, Glen, et al.
Created Date
2020

Blockchain technology enables a distributed and decentralized environment without any central authority. Healthcare is one industry in which blockchain is expected to have significant impacts. In recent years, the Healthcare Information Exchange(HIE) has been shown to benefit the healthcare industry remarkably. It has been shown that blockchain could help to improve multiple aspects of the HIE system. When Blockchain technology meets HIE, there are only a few proposed systems and they all suffer from the following two problems. First, the existing systems are not patient-centric in terms of data governance. Patients do not own their data and have no direct …

Contributors
Vishnoi, Manish, Boscovic, Dragan, Candan, Kasim S, et al.
Created Date
2020

Speech is known to serve as an early indicator of neurological decline, particularly in motor diseases. There is significant interest in developing automated, objective signal analytics that detect clinically-relevant changes and in evaluating these algorithms against the existing gold-standard: perceptual evaluation by trained speech and language pathologists. Hypernasality, the result of poor control of the velopharyngeal flap---the soft palate regulating airflow between the oral and nasal cavities---is one such speech symptom of interest, as precise velopharyngeal control is difficult to achieve under neuromuscular disorders. However, a host of co-modulating variables give hypernasal speech a complex and highly variable acoustic signature, …

Contributors
Saxon, Michael Stephen, Berisha, Visar, Panchanathan, Sethuraman, et al.
Created Date
2020

Due to the advent of easy-to-use, portable, and cost-effective brain signal sensing devices, pervasive Brain-Machine Interface (BMI) applications using Electroencephalogram (EEG) are growing rapidly. The main objectives of these applications are: 1) pervasive collection of brain data from multiple users, 2) processing the collected data to recognize the corresponding mental states, and 3) providing real-time feedback to the end users, activating an actuator, or information harvesting by enterprises for further services. Developing BMI applications faces several challenges, such as cumbersome setup procedure, low signal-to-noise ratio, insufficient signal samples for analysis, and long processing times. Internet-of-Things (IoT) technologies provide the opportunity …

Contributors
Sadeghi Oskooyee, Seyed Koosha, Gupta, Sandeep K S, Santello, Marco, et al.
Created Date
2020

This thesis introduces new techniques for clustering distributional data according to their geometric similarities. This work builds upon the optimal transportation (OT) problem that seeks global minimum cost for matching distributional data and leverages the connection between OT and power diagrams to solve different clustering problems. The OT formulation is based on the variational principle to differentiate hard cluster assignments, which was missing in the literature. This thesis shows multiple techniques to regularize and generalize OT to cope with various tasks including clustering, aligning, and interpolating distributional data. It also discusses the connections of the new formulation to other OT …

Contributors
Mi, Liang, Wang, Yalin, Chen, Kewei, et al.
Created Date
2020

Positron emission tomography (PET) is a non-invasive molecular imaging technique widely used for the quantification of physiological and biochemical processes in preclinical and clinical research. Due to its fundamental role in the health care system, there is a constant need for improvement and optimization of its scanner systems and protocols leading to a dedicated active area of research for PET. (Geant4 Application for Tomographic Emission (GATE) is a simulation platform designed to model and analyze a medical device. Monte Carlo simulations are essential tools to assist in optimizing the data acquisition protocols or in evaluating the correction methods for improved …

Contributors
Thirumalai, Sowmiya Raj, Vasileska, Dragica, Goldan, Amirhossein, et al.
Created Date
2020

Societal infrastructure is built with vision at the forefront of daily life. For those with severe visual impairments, this creates countless barriers to the participation and enjoyment of life’s opportunities. Technological progress has been both a blessing and a curse in this regard. Digital text together with screen readers and refreshable Braille displays have made whole libraries readily accessible and rideshare tech has made independent mobility more attainable. Simultaneously, screen-based interactions and experiences have only grown in pervasiveness and importance, precluding many of those with visual impairments. Sensory Substituion, the process of substituting an unavailable modality with another one, has …

Contributors
Fakhri, Bijan, Panchanathan, Sethuraman, McDaniel, Troy L, et al.
Created Date
2020

In a multi-robot system, locating a team robot is an important issue. If robots can refer to the location of team robots based on information through passive action recognition without explicit communication, various advantages (e.g. improving security for military purposes) can be obtained. Specifically, when team robots follow the same motion rule based on information about adjacent robots, associations can be found between robot actions. If the association can be analyzed, this can be a clue to the remote robot. Using these clues, it is possible to infer remote robots which are outside of the sensor range. In this paper, …

Contributors
Kang, Sehyeok, Pavlic, Theodore P, Richa, Andrea W, et al.
Created Date
2020

Driving is the coordinated operation of mind and body for movement of a vehicle, such as a car, or a bus. Driving, being considered an everyday activity for many people, still has an issue of safety. Driver distraction is becoming a critical safety problem. Speed, drunk driving as well as distracted driving are the three leading factors in the fatal car crashes. Distraction, which is defined as an excessive workload and limited attention, is the main paradigm that guides this research area. Driver behavior analysis can be used to address the distraction problem and provide an intelligent adaptive agent to …

Contributors
Monjezi Kouchak, Shokoufeh, Gaffar, Ashraf, Doupe, Adam, et al.
Created Date
2020

The mobile crowdsensing (MCS) applications leverage the user data to derive useful information by data-driven evaluation of innovative user contexts and gathering of information at a high data rate. Such access to context-rich data can potentially enable computationally intensive crowd-sourcing applications such as tracking a missing person or capturing a highlight video of an event. Using snippets and pictures captured from multiple mobile phone cameras with specific contexts can improve the data acquired in such applications. These MCS applications require efficient processing and analysis to generate results in real time. A human user, mobile device and their interactions cause a …

Contributors
Pore, Madhurima, GUPTA, SANDEEP K. S., GUPTA, SANDEEP K. S., et al.
Created Date
2019