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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.


Subject
Date Range
2011 2019


Data imbalance and data noise often coexist in real world datasets. Data imbalance affects the learning classifier by degrading the recognition power of the classifier on the minority class, while data noise affects the learning classifier by providing inaccurate information and thus misleads the classifier. Because of these differences, data imbalance and data noise have been treated separately in the data mining field. Yet, such approach ignores the mutual effects and as a result may lead to new problems. A desirable solution is to tackle these two issues jointly. Noting the complementary nature of generative and discriminative models, this research …

Contributors
He, Miao, Wu, Teresa, Li, Jing, et al.
Created Date
2014

The Arizona State University Herbarium began in 1896 when Professor Fredrick Irish collected the first recorded Arizona specimen for what was then called the Tempe Normal School - a Parkinsonia microphylla. Since then, the collection has grown to approximately 400,000 specimens of vascular plants and lichens. The most recent project includes the digitization - both the imaging and databasing - of approximately 55,000 vascular plant specimens from Latin America. To accomplish this efficiently, possibilities in non-traditional methods, including both new and existing technologies, were explored. SALIX (semi-automatic label information extraction) was developed as the central tool to handle automatic parsing, …

Contributors
Barber, Anne Christine, Landrum, Leslie R., Wojciechowski, Martin F., et al.
Created Date
2012

This work involved the analysis of a public health system, and the design, development and deployment of enterprise informatics architecture, and sustainable community methods to address problems with the current public health system. Specifically, assessment of the Nationally Notifiable Disease Surveillance System (NNDSS) was instrumental in forming the design of the current implementation at the Southern Nevada Health District (SNHD). The result of the system deployment at SNHD was considered as a basis for projecting the practical application and benefits of an enterprise architecture. This approach has resulted in a sustainable platform to enhance the practice of public health by …

Contributors
Kriseman, Jeffrey Michael, Dinu, Valentin, Greenes, Robert, et al.
Created Date
2012

Law enforcement, schools and universities, health service agencies, as well as social service agencies, each acquire information from individuals that receive their services. That information gets recorded into the respective application system of each organization. The information, however, gets recorded only in the context of each service rendered and within each system used to record it. Information that is recorded by the police department for one individual is entirely different from the information that is recorded by the hospital for that same individual. What if all the organizations used the same system to record information? What if all the organizations …

Contributors
Pullin, Britton Scott, Schildgen, Thomas, Prewitt, Deborah, et al.
Created Date
2012

The increasing volume and complexity of software systems and the growing demand of programming skills calls for efficient information retrieval techniques from source code documents. Programming related information seeking is often challenging for users facing constraints in knowledge and experience. Source code documents contain multi-faceted semi-structured text, having different levels of semantic information like syntax, blueprints, interfaces, flow graphs, dependencies and design patterns. Matching user queries optimally across these levels is a major challenge for information retrieval systems. Code recommendations can help information seeking and retrieval by pro-actively sampling similar examples based on the users context. These recommendations can be …

Contributors
Singh, Shashank Hansraj, Hsiao, I-Han, Walker, Erin, et al.
Created Date
2017

Recommender systems are a type of information filtering system that suggests items that may be of interest to a user. Most information retrieval systems have an overwhelmingly large number of entries. Most users would experience information overload if they were forced to explore the full set of results. The goal of recommender systems is to overcome this limitation by predicting how users will value certain items and returning the items that should be of the highest interest to the user. Most recommender systems collect explicit user feedback, such as a rating, and attempt to optimize their model to this rating …

Contributors
Ackerman, Brian, Chen, Yi, Candan, Kasim, et al.
Created Date
2012

Social media has become the norm of everyone for communication. The usage of social media has increased exponentially in the last decade. The myriads of Social media services such as Facebook, Twitter, Snapchat, and Instagram etc allow people to connect with their friends, and followers freely. The attackers who try to take advantage of this situation has also increased at an exponential rate. Every social media service has its own recommender systems and user profiling algorithms. These algorithms use users current information to make different recommendations. Often the data that is formed from social media services is Linked data as …

Contributors
Magham, Venkatesh, Liu, Huan, Wu, Liang, et al.
Created Date
2019

One of the greatest 21st century challenges is meeting the needs of a growing world population expected to increase 35% by 2050 given projected trends in diets, consumption and income. This in turn requires a 70-100% improvement on current production capability, even as the world is undergoing systemic climate pattern changes. This growth not only translates to higher demand for staple products, such as rice, wheat, and beans, but also creates demand for high-value products such as fresh fruits and vegetables (FVs), fueled by better economic conditions and a more health conscious consumer. In this case, it would seem that …

Contributors
Flores, Hector M., Villalobos, Rene, Pan, Rong, et al.
Created Date
2017

Social discounting underlies individual altruistic decision-making, and it is frequently measured as the amount of hypothetical money one is willing to forgo for another person as a function of social distance. In the classic social discounting task, individual participants are asked to imagine their friends along a continuum of social distance, that is then used to estimate participant’s social discounting rate. While an ever-growing proportion of social interactions takes place over social media, no research has yet characterized social discounting in that context. Moreover, no research has estimated social discounting rate using real persons’ social distance, instead of the hypothetical …

Contributors
Jiang, Linle, Miller, Paul A, Robles-Sotelo, Elias, et al.
Created Date
2018

This study explores the impact of feedback and feedforward and personality on computer-mediated behavior change. The impact of the effects were studied using subjects who entered information relevant to their diet and exercise into an online tool. Subjects were divided into four experimental groups: those receiving only feedback, those receiving only feedforward, those receiving both, and those receiving none. Results were analyzed using regression analysis. Results indicate that both feedforward and feedback impact behavior change and that individuals with individuals ranking low in conscientiousness experienced behavior change equivalent to that of individuals with high conscientiousness in the presence of feedforward …

Contributors
Mccreless, Tamuchin, St. Louis, Robert, St. Louis, Robert D, et al.
Created Date
2012