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.
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Description
The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a large amount of data is cheap and easy, annotating them with class labels is an expensive process in terms of time, labor and human expertise. This has paved the way for research in the field of active learning. Such algorithms automatically select the salient and exemplar instances from large quantities of unlabeled data and are effective in reducing human labeling effort in inducing classification models. To utilize the possible presence of multiple labeling agents, there have been attempts towards a batch mode form of active learning, where a batch of data instances is selected simultaneously for manual annotation. This dissertation is aimed at the development of novel batch mode active learning algorithms to reduce manual effort in training classification models in real world multimedia pattern recognition applications. Four major contributions are proposed in this work: $(i)$ a framework for dynamic batch mode active learning, where the batch size and the specific data instances to be queried are selected adaptively through a single formulation, based on the complexity of the data stream in question, $(ii)$ a batch mode active learning strategy for fuzzy label classification problems, where there is an inherent imprecision and vagueness in the class label definitions, $(iii)$ batch mode active learning algorithms based on convex relaxations of an NP-hard integer quadratic programming (IQP) problem, with guaranteed bounds on the solution quality and $(iv)$ an active matrix completion algorithm and its application to solve several variants of the active learning problem (transductive active learning, multi-label active learning, active feature acquisition and active learning for regression). These contributions are validated on the face recognition and facial expression recognition problems (which are commonly encountered in real world applications like robotics, security and assistive technology for the blind and the visually impaired) and also on collaborative filtering applications like movie recommendation.
ContributorsChakraborty, Shayok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Balasubramanian, Vineeth N. (Committee member) / Li, Baoxin (Committee member) / Mittelmann, Hans (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a reputation score for each tweet that is based not just on content, but also additional information from the Twitter ecosystem that consists of users, tweets, and the web pages that tweets link to. This information is obtained by modeling the Twitter ecosystem as a three-layer graph. The reputation score is used to power two novel methods of ranking tweets by propagating the reputation over an agreement graph based on tweets' content similarity. Additionally, I show how the agreement graph helps counter tweet spam. An evaluation of my method on 16~million tweets from the TREC 2011 Microblog Dataset shows that it doubles the precision over baseline Twitter Search and achieves higher precision than current state of the art method. I present a detailed internal empirical evaluation of RAProp in comparison to several alternative approaches proposed by me, as well as external evaluation in comparison to the current state of the art method.
ContributorsRavikumar, Srijith (Author) / Kambhampati, Subbarao (Thesis advisor) / Davulcu, Hasan (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Objective of this thesis project is to build a prototype using Linear Temporal Logic specifications for generating a 2D motion plan commanding an iRobot to fulfill the specifications. This thesis project was created for Cyber Physical Systems Lab in Arizona State University. The end product of this thesis is creation of a software solution which can be used in the academia and industry for research in cyber physical systems related applications. The major features of the project are: creating a modular system for motion planning, use of Robot Operating System (ROS), use of triangulation for environment decomposition and using stargazer sensor for localization. The project is built on an open source software called ROS which provides an environment where it is very easy to integrate different modules be it software or hardware on a Linux based platform. Use of ROS implies the project or its modules can be adapted quickly for different applications as the need arises. The final software package created and tested takes a data file as its input which contains the LTL specifications, a symbols list used in the LTL and finally the environment polygon data containing real world coordinates for all polygons and also information on neighbors and parents of each polygon. The software package successfully ran the experiment of coverage, reachability with avoidance and sequencing.
ContributorsPandya, Parth (Author) / Fainekos, Georgios (Thesis advisor) / Dasgupta, Partha (Committee member) / Lee, Yann-Hang (Committee member) / Arizona State University (Publisher)
Created2013
Description
Linear Temporal Logic is gaining increasing popularity as a high level specification language for robot motion planning due to its expressive power and scalability of LTL control synthesis algorithms. This formalism, however, requires expert knowledge and makes it inaccessible to non-expert users. This thesis introduces a graphical specification environment to create high level motion plans to control robots in the field by converting a visual representation of the motion/task plan into a Linear Temporal Logic (LTL) specification. The visual interface is built on the Android tablet platform and provides functionality to create task plans through a set of well defined gestures and on screen controls. It uses the notion of waypoints to quickly and efficiently describe the motion plan and enables a variety of complex Linear Temporal Logic specifications to be described succinctly and intuitively by the user without the need for the knowledge and understanding of LTL specification. Thus, it opens avenues for its use by personnel in military, warehouse management, and search and rescue missions. This thesis describes the construction of LTL for various scenarios used for robot navigation using the visual interface developed and leverages the use of existing LTL based motion planners to carry out the task plan by a robot.
ContributorsSrinivas, Shashank (Author) / Fainekos, Georgios (Thesis advisor) / Baral, Chitta (Committee member) / Burleson, Winslow (Committee member) / Arizona State University (Publisher)
Created2013
Description
Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to its modeling language in order to enhance expressivity, such as incorporating aggregates and interfaces with ontologies. Also, in order to overcome the grounding bottleneck of computation in ASP, there are increasing interests in integrating ASP with other computing paradigms, such as Constraint Programming (CP) and Satisfiability Modulo Theories (SMT). Due to the non-monotonic nature of the ASP semantics, such enhancements turned out to be non-trivial and the existing extensions are not fully satisfactory. We observe that one main reason for the difficulties rooted in the propositional semantics of ASP, which is limited in handling first-order constructs (such as aggregates and ontologies) and functions (such as constraint variables in CP and SMT) in natural ways. This dissertation presents a unifying view on these extensions by viewing them as instances of formulas with generalized quantifiers and intensional functions. We extend the first-order stable model semantics by by Ferraris, Lee, and Lifschitz to allow generalized quantifiers, which cover aggregate, DL-atoms, constraints and SMT theory atoms as special cases. Using this unifying framework, we study and relate different extensions of ASP. We also present a tight integration of ASP with SMT, based on which we enhance action language C+ to handle reasoning about continuous changes. Our framework yields a systematic approach to study and extend non-monotonic languages.
ContributorsMeng, Yunsong (Author) / Lee, Joohyung (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Baral, Chitta (Committee member) / Fainekos, Georgios (Committee member) / Lifschitz, Vladimir (Committee member) / Arizona State University (Publisher)
Created2013
Description
The signing of the No Child Left Behind Act in 2001 created a need for Title 1 principals to conceptualize and operationalize parent engagement. This study examines how three urban principals in Arizona implemented the mandates of the Act as it pertains to parent involvement. The purpose of this qualitative case study is to examine how principals operationalize and conceptualize parent involvement as they navigate barriers and laws particular to the state of Arizona. This study sought to understand issues surrounding parent involvement in Title 1 schools in Arizona. The beliefs and interview dialogue of the principals as it pertains to parent engagement provided an understanding of how urban principals in Arizona implement the aspects of No Child Left Behind Act that deal with parent involvement. The research study concluded that parents have community cultural wealth that contributes to the success of the students of engaged parents and that cultural responsive leadership assists principals with engaging parents in their schools. The research concludes that a gap exists between how parents and principals perceive and construct parent engagement versus what is prescribed in No Child Left Behind Act.
ContributorsConley, Loraine (Author) / Brayboy, Bryan (Thesis advisor) / Mccarty, Teresa (Committee member) / Scott, Kimberly (Committee member) / Arizona State University (Publisher)
Created2012
Description
The purpose of the research study was to explore the perceptions of Navajo mothers and Navajo fathers in the development and childrearing practices of their children and to what extent each parent was involved in their children by gender and age. The objective of the interviews was to capture the perceptions of each parent as to child development and childrearing practices as well as the beliefs that they have on parental involvement. In the current study, the interviews provided information regarding attitudes and perceptions of parental involvement from the Navajo mothers and the Navajo fathers who participated in the study. By using probing questions, deeper insights into the understanding and perceptions of parental involvement were obtained.
ContributorsTsosie, Berdina (Author) / Appleton, Nicholas A (Thesis advisor) / Spencer, Dee A (Committee member) / Duplissis, Mark (Committee member) / Arizona State University (Publisher)
Created2012
Description
This thesis introduces the Model-Based Development of Multi-iRobot Toolbox (MBDMIRT), a Simulink-based toolbox designed to provide the means to acquire and practice the Model-Based Development (MBD) skills necessary to design real-time embedded system. The toolbox was developed in the Cyber-Physical System Laboratory at Arizona State University. The MBDMIRT toolbox runs under MATLAB/Simulink to simulate the movements of multiple iRobots and to control, after verification by simulation, multiple physical iRobots accordingly. It adopts the Simulink/Stateflow, which exemplifies an approach to MBD, to program the behaviors of the iRobots. The MBDMIRT toolbox reuses and augments the open-source MATLAB-Based Simulator for the iRobot Create from Cornell University to run the simulation. Regarding the mechanism of iRobot control, the MBDMIRT toolbox applies the MATLAB Toolbox for the iRobot Create (MTIC) from United States Naval Academy to command the physical iRobots. The MBDMIRT toolbox supports a timer in both the simulation and the control, which is based on the local clock of the PC running the toolbox. In addition to the build-in sensors of an iRobot, the toolbox can simulate four user-added sensors, which are overhead localization system (OLS), sonar sensors, a camera, and Light Detection And Ranging (LIDAR). While controlling a physical iRobot, the toolbox supports the StarGazer OLS manufactured by HAGISONIC, Inc.
ContributorsSu, Shih-Kai (Author) / Fainekos, Georgios E (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Artemiadis, Panagiotis K (Committee member) / Arizona State University (Publisher)
Created2012
Description
As a result of the district program evaluation, a follow up on teacher perceptions of an online collaboration versus face to face collaboration approach was deemed necessary. The interviews were conducted with eight teachers from a suburban southwest K-8 public school district. After all teachers had participated in a 10 week program evaluation comparing online team teacher collaboration with face-to-face team teacher collaboration, the interview process began. One teacher from each grade level team was randomly selected to participate in the interview process. Analysis of the interview responses was inconclusive. Findings were confounded by the apparent lack of understanding of major concepts of Professional Learning Communities on the part of the participants. Assumptions about participant knowledge must be tested prior to investigations of the influence of either face to face or online format as delivery modes.
ContributorsTucker, Pamela K (Author) / McCoy, Kathleen (Thesis advisor) / Gehrke, Rebecca (Committee member) / Ham, Timothy (Committee member) / Arizona State University (Publisher)
Created2013
Descriptionno
ContributorsTrujillo, Gabriel (Author) / Powers, Jeanne (Thesis advisor) / Fischman, Gustavo E. (Committee member) / Baracy, John (Committee member) / Arizona State University (Publisher)
Created2012