Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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Description
The relationship between biodiversity and ecosystem functioning (BEF) is a central issue in ecology, and a number of recent field experimental studies have greatly improved our understanding of this relationship. Spatial heterogeneity is a ubiquitous characterization of ecosystem processes, and has played a significant role in shaping BEF relationships. The first step towards understanding the effects of spatial heterogeneity on the BEF relationships is to quantify spatial heterogeneity characteristics of key variables of biodiversity and ecosystem functioning, and identify the spatial relationships among these variables. The goal of our research was to address the following research questions based on data collected in 2005 (corresponding to the year when the initial site background information was conducted) and in 2008 (corresponding to the year when removal treatments were conducted) from the Inner Mongolia Grassland Removal Experiment (IMGRE) located in northern China: 1) What are the spatial patterns of soil nutrients, plant biodiversity, and aboveground biomass in a natural grassland community of Inner Mongolia, China? How are they related spatially? and 2) How do removal treatments affect the spatial patterns of soil nutrients, plant biodiversity, and aboveground biomass? Is there any change for their spatial correlations after removal treatments? Our results showed that variables of biodiversity and ecosystem functioning in the natural grassland community would present different spatial patterns, and they would be spatially correlated to each other closely. Removal treatments had a significant effect on spatial structures and spatial correlations of variables, compared to those prior to the removal treatments. The differences in spatial pattern of plant and soil variables and their correlations before and after the biodiversity manipulation may not imply that the results from BEF experiments like IMGRE are invalid. However, they do suggest that the possible effects of spatial heterogeneity on the BEF relationships should be critically evaluated in future studies.
ContributorsYuan, Fei (Author) / Wu, Jianguo (Thesis advisor) / Smith, Andrew T. (Committee member) / Rowe, Helen I (Committee member) / Arizona State University (Publisher)
Created2011
Description
Many products undergo several stages of testing ranging from tests on individual components to end-item tests. Additionally, these products may be further "tested" via customer or field use. The later failure of a delivered product may in some cases be due to circumstances that have no correlation with the product's inherent quality. However, at times, there may be cues in the upstream test data that, if detected, could serve to predict the likelihood of downstream failure or performance degradation induced by product use or environmental stresses. This study explores the use of downstream factory test data or product field reliability data to infer data mining or pattern recognition criteria onto manufacturing process or upstream test data by means of support vector machines (SVM) in order to provide reliability prediction models. In concert with a risk/benefit analysis, these models can be utilized to drive improvement of the product or, at least, via screening to improve the reliability of the product delivered to the customer. Such models can be used to aid in reliability risk assessment based on detectable correlations between the product test performance and the sources of supply, test stands, or other factors related to product manufacture. As an enhancement to the usefulness of the SVM or hyperplane classifier within this context, L-moments and the Western Electric Company (WECO) Rules are used to augment or replace the native process or test data used as inputs to the classifier. As part of this research, a generalizable binary classification methodology was developed that can be used to design and implement predictors of end-item field failure or downstream product performance based on upstream test data that may be composed of single-parameter, time-series, or multivariate real-valued data. Additionally, the methodology provides input parameter weighting factors that have proved useful in failure analysis and root cause investigations as indicators of which of several upstream product parameters have the greater influence on the downstream failure outcomes.
ContributorsMosley, James (Author) / Morrell, Darryl (Committee member) / Cochran, Douglas (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Roberts, Chell (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
Description
Infectious diseases are a leading cause of death worldwide. With the development of drugs, vaccines and antibiotics, it was believed that for the first time in human history diseases would no longer be a major cause of mortality. Newly emerging diseases, re-emerging diseases and the emergence of microorganisms resistant to existing treatment have forced us to re-evaluate our optimistic perspective. In this study, a simple mathematical framework for super-infection is considered in order to explore the transmission dynamics of drug-resistance. Through its theoretical analysis, we identify the conditions necessary for the coexistence between sensitive strains and drug-resistant strains. Farther, in order to investigate the effectiveness of control measures, the model is extended so as to include vaccination and treatment. The impact that these preventive and control measures may have on its disease dynamics is evaluated. Theoretical results being confirmed via numerical simulations. Our theoretical results on two-strain drug-resistance models are applied in the context of Malaria, antimalarial drugs, and the administration of a possible partially effective vaccine. The objective is to develop a monitoring epidemiological framework that help evaluate the impact of antimalarial drugs and partially-effective vaccine in reducing the disease burden at the population level. Optimal control theory is applied in the context of this framework in order to assess the impact of time dependent cost-effective treatment efforts. It is shown that cost-effective combinations of treatment efforts depend on the population size, cost of implementing treatment controls, and the parameters of the model. We use these results to identify optimal control strategies for several scenarios.
ContributorsUrdapilleta, Alicia (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Wang, Xiaohong (Thesis advisor) / Wirkus, Stephen (Committee member) / Camacho, Erika (Committee member) / Arizona State University (Publisher)
Created2011
Description
Worldwide, riverine floodplains are among the most endangered landscapes. In response to anthropogenic impacts, riverine restoration projects are considerably increasing. However, there is a paucity of information on how riparian rehabilitation activities impact non-avian wildlife communities. I evaluated herpetofauna abundance, species richness, diversity (i.e., Shannon and Simpson indices), species-specific responses, and riparian microhabitat characteristics along three reaches (i.e., wildland, urban rehabilitated, and urban disturbed) of the Salt River, Arizona. The surrounding uplands of the two urbanized reaches were dominated by the built environment (i.e., Phoenix metropolitan area). I predicted that greater diversity of microhabitat and lower urbanization would promote herpetofauna abundance, richness, and diversity. In 2010, at each reach, I performed herpetofauna visual surveys five times along eight transects (n=24) spanning the riparian zone. I quantified twenty one microhabitat characteristics such as ground substrate, vegetative cover, woody debris, tree stem density, and plant species richness along each transect. Herpetofauna species richness was the greatest along the wildland reach, and the lowest along the urban disturbed reach. The wildland reach had the greatest diversity indices, and diversity indices of the two urban reaches were similar. Abundance of herpetofauna was approximately six times lower along the urban disturbed reach compared to the two other reaches, which had similar abundances. Principal Component Analysis (PCA) reduced microhabitat variables to five factors, and significant differences among reaches were detected. Vegetation structure complexity, vegetation species richness, as well as densities of Prosopis (mesquite), Salix (willow), Populus (cottonwood), and animal burrows had a positive correlation with at least one of the three herpetofauna community parameter quantified (i.e., herpetofauna abundance, species richness, and diversity indices), and had a positive correlation with at least one herpetofauna species. Overall, rehabilitation activities positively influenced herpetofauna abundance and species richness, whereas urbanization negatively influenced herpetofauna diversity indices. Based on herpetofauna/microhabitat correlations established, I developed recommendations regarding microhabitat features that should be created in order to promote herpetofauna when rehabilitating degraded riparian systems. Recommendations are to plant vegetation of different growth habit, provide woody debris, plant Populus, Salix, and Prosopis of various ages and sizes, and to promote small mammal abundance.
ContributorsBanville, Mélanie Josianne (Author) / Bateman, Heather L (Thesis advisor) / Brady, Ward (Committee member) / Stromberg, Juliet (Committee member) / Arizona State University (Publisher)
Created2011
Description
Diseases have been part of human life for generations and evolve within the population, sometimes dying out while other times becoming endemic or the cause of recurrent outbreaks. The long term influence of a disease stems from different dynamics within or between pathogen-host, that have been analyzed and studied by many researchers using mathematical models. Co-infection with different pathogens is common, yet little is known about how infection with one pathogen affects the host's immunological response to another. Moreover, no work has been found in the literature that considers the variability of the host immune health or that examines a disease at the population level and its corresponding interconnectedness with the host immune system. Knowing that the spread of the disease in the population starts at the individual level, this thesis explores how variability in immune system response within an endemic environment affects an individual's vulnerability, and how prone it is to co-infections. Immunology-based models of Malaria and Tuberculosis (TB) are constructed by extending and modifying existing mathematical models in the literature. The two are then combined to give a single nine-variable model of co-infection with Malaria and TB. Because these models are difficult to gain any insight analytically due to the large number of parameters, a phenomenological model of co-infection is proposed with subsystems corresponding to the individual immunology-based model of a single infection. Within this phenomenological model, the variability of the host immune health is also incorporated through three different pathogen response curves using nonlinear bounded Michaelis-Menten functions that describe the level or state of immune system (healthy, moderate and severely compromised). The immunology-based models of Malaria and TB give numerical results that agree with the biological observations. The Malaria--TB co-infection model gives reasonable results and these suggest that the order in which the two diseases are introduced have an impact on the behavior of both. The subsystems of the phenomenological models that correspond to a single infection (either of Malaria or TB) mimic much of the observed behavior of the immunology-based counterpart and can demonstrate different behavior depending on the chosen pathogen response curve. In addition, varying some of the parameters and initial conditions in the phenomenological model yields a range of topologically different mathematical behaviors, which suggests that this behavior may be able to be observed in the immunology-based models as well. The phenomenological models clearly replicate the qualitative behavior of primary and secondary infection as well as co-infection. The mathematical solutions of the models correspond to the fundamental states described by immunologists: virgin state, immune state and tolerance state. The phenomenological model of co-infection also demonstrates a range of parameter values and initial conditions in which the introduction of a second disease causes both diseases to grow without bound even though those same parameters and initial conditions did not yield unbounded growth in the corresponding subsystems. This results applies to all three states of the host immune system. In terms of the immunology-based system, this would suggest the following: there may be parameter values and initial conditions in which a person can clear Malaria or TB (separately) from their system but in which the presence of both can result in the person dying of one of the diseases. Finally, this thesis studies links between epidemiology (population level) and immunology in an effort to assess the impact of pathogen's spread within the population on the immune response of individuals. Models of Malaria and TB are proposed that incorporate the immune system of the host into a mathematical model of an epidemic at the population level.
ContributorsSoho, Edmé L (Author) / Wirkus, Stephen (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2011
Description
Artificial Intelligence’s facial recognition programs are inherently racially biased. The programs are not necessarily created with the intent to disproportionately impact marginalized communities, but through their data mining process of learning, they can become biased as the data they use may train them to think in a biased manner. Biased data is difficult to spot as the programming field is homogeneous and this issue reflects underlying societal biases. Facial recognition programs do not identify minorities at the same rate as their Caucasian counterparts leading to false positives in identifications and an increase of run-ins with the law. AI does not have the ability to role-reverse judge as a human does and therefore its use should be limited until a more equitable program is developed and thoroughly tested.
ContributorsGurtler, Charles William (Author) / Iheduru, Okechukwu (Thesis director) / Fette, Donald (Committee member) / Economics Program in CLAS (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Robots are often used in long-duration scenarios, such as on the surface of Mars,where they may need to adapt to environmental changes. Typically, robots have been built specifically for single tasks, such as moving boxes in a warehouse or surveying construction sites. However, there is a modern trend away from human hand-engineering and toward robot learning. To this end, the ideal robot is not engineered,but automatically designed for a specific task. This thesis focuses on robots which learn path-planning algorithms for specific environments. Learning is accomplished via genetic programming. Path-planners are represented as Python code, which is optimized via Pareto evolution. These planners are encouraged to explore curiously and efficiently. This research asks the questions: “How can robots exhibit life-long learning where they adapt to changing environments in a robust way?”, and “How can robots learn to be curious?”.
ContributorsSaldyt, Lucas P (Author) / Ben Amor, Heni (Thesis director) / Pavlic, Theodore (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This paper is centered on the use of generative adversarial networks (GANs) to convert or generate RGB images from grayscale ones. The primary goal is to create sensible and colorful versions of a set of grayscale images by training a discriminator to recognize failed or generated images and training a generator to attempt to satisfy the discriminator. The network design is described in further detail below; however there are several potential issues that arise including the averaging of a color for certain images such that small details in an image are not assigned unique colors leading to a neutral blend. We attempt to mitigate this issue as much as possible.
ContributorsLobo, Ian (Co-author) / Koleber, Keith (Co-author) / Markabawi, Jah (Co-author) / Masud, Abdullah (Co-author) / Yang, Yingzhen (Thesis director) / Wang, Yancheng (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This study was designed to produce a comprehensive flora of Usery Mountain Regional Park and Pass Mountain of the Tonto National Forest. A total of 168 vascular plant species representing 46 families and 127 genera were collected or documented at this study area. Sixteen species were not native to the flora of Arizona and represent 9.5% of the flora. Nevertheless, the study area does not appear to be significantly damaged or degraded in spite of its historical and current land use. The location and types of invasive species recorded in this study will assist with implementing preventative measures to prevent further spreading of certain species. The complete list of all vascular species recorded in this study will provide a valuable tool for land management decisions and future restoration projects that may occur at this area or similar sites and invasive species control. The distribution of the saguaro (Carnegiea gigantea) population on Pass Mountain was documented through the measurement of saguaros by random sampling. ArcGIS was used to generate 50 random points for sampling the saguaro population. Analysis to determine saguaro habitat preferences based on the parameters of aspect, slope and elevation was conducted through ArcGIS. The saguaro population of Pass Mountain significantly favored the southern aspects with the highest concentration occurring in the southwest aspects at an average density of 42.66 saguaros per hectare. The large numbers of saguaros recorded in the younger size classes suggests a growing populations.
ContributorsMarshall, Laura Lee (Author) / Steele, Kelly P (Thesis advisor) / Miller, William H. (Committee member) / Alford, Eddie J (Committee member) / Arizona State University (Publisher)
Created2011
Description
Non-native saltcedar (Tamarix spp.) has invaded many riparian communities and is the third most abundant tree in Southwestern riparian areas. I evaluated lizard populations and microhabitat selection during 2009 and 2010 along the Virgin River in Nevada and Arizona to determine the impact of saltcedar. Along the riparian corridor, I observed common side-blotched lizards (Uta stansburiana) within two vegetation types: monotypic non-native saltcedar stands or mixed stands of cottonwood (Populus fremontii), willow (Salix spp.), mesquite (Prosopis spp.) and saltcedar. I predicted that population parameters such as body condition, adult to hatchling ratio, abundance, and persistence would vary among vegetation types. Also, I predicted the presence of saltcedar influences how lizards utilize available habitat. Lizard population parameters were obtained from a mark-recapture study in which I captured 233 individual lizards. I examined habitat selection and habitat availability using visual encounter surveys (VES) for lizards and recorded 11 microhabitat variables where 16 lizards were found. I found no significant difference in population parameters between mixed and non-native saltcedar communities. However, population parameters were negatively correlated with canopy cover. I found that lizards selected habitat with low understory and canopy cover regardless of vegetation type. My results indicate that lizards utilize similar structural characteristics in both mixed and non-native vegetation. Understanding impacts of saltcedar on native fauna is important for managers who are tasked with control and management of this non-native species.
ContributorsNielsen, Danny (Author) / Bateman, Heather L. (Thesis advisor) / Miller, William H. (Committee member) / Sullivan, Brian K. (Committee member) / Arizona State University (Publisher)
Created2011