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.
Filtering by
- Creators: Bansal, Ajay
- Creators: Abbaszadegan, Morteza
This thesis deals with evaluating the performance of Presto in processing big RDF data against Apache Hive. A comparative analysis was also conducted against 4store, a native RDF store. To evaluate the performance Presto for big RDF data processing, a map-reduce program and a compiler, based on Flex and Bison, were implemented. The map-reduce program loads RDF data into HDFS while the compiler translates SPARQL queries into a subset of SQL that Presto (and Hive) can understand. The evaluation was done on four and eight node Linux clusters installed on Microsoft Windows Azure platform with RDF datasets of size 10, 20, and 30 million triples. The results of the experiment show that Presto has a much higher performance than Hive can be used to process big RDF data. The thesis also proposes an architecture based on Presto, Presto-RDF, that can be used to process big RDF data.
This study focuses on one such pathogen Legionella pneumophila which is resistant to environmental stressors and treatment conditions. It is also responsible for Legionnaires' disease outbreak through drinking water thus attracting attention of regulatory agencies. The work assessed the attachment and colonization of Legionella and heterotrophic bacteria in lab scale GAC media column filters. Quantification of Legionella and HPC in the influent, effluent, column's biofilms and on the GAC particles was performed over time using fluorescent microscopy and culture based techniques.
The results indicated gradual increase in the colonization of the GAC particles with HPC bacteria. Initially high number of Legionella cells were detected in the column effluent and were not detected on GAC suggesting low attachment of the cells to the particles potentially due to lack of any previous biofilms. With the initial colonization of the filter media by other bacteria the number of Legionella cells on the GAC particles and biofilms also increased. Presence of Legionella was confirmed in all the samples collected from the columns spiked with Legionella. Significant increase in the Legionella was observed in column's inner surface biofilm (0.25 logs up to 0.52 logs) and on GAC particles (0.42 logs up to 0.63 logs) after 2 months. Legionella and HPC attached to column's biofilm were higher than that on GAC particles indicating the strong association with biofilms. The bacterial concentration slowly increased in the effluent. This may be due to column's wall effect decreasing filter efficiency, possible exhaustion of GAC capacity over time and potential bacterial growth.
The pilot-scale, column study produced novel results which demonstrated the mechanism for Legionella to be transported through recharge basin soil. E. coli was transported, through 122 cm of the media in under 6 hours, whereas, Legionella was transported, through the same distance, in under 30 hours. Legionella has been shown to survive in low nutrient conditions for over a year. Given the novel results of this proof of concept study, a claim can be made for the transport of Legionella into groundwater aquifers through engineering recharge basin conditions, in Central Arizona.