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
- All Subjects: Electrical Engineering
- Creators: Thornton, Trevor
Simultaneous segmentation and feature extraction approaches for silicon-pores sensor data are considered. Aggregating data into a matrix and performing low rank and sparse matrix decompositions with additional smoothness constraints are proposed to solve this problem. Comparison of several variants of the approaches and results for signal de-noising and translocation/trapping event extraction are presented. Algorithms to improve transform-domain features for ion-channel time-series signals based on matrix completion are presented. The improved features achieve better performance in classification tasks and in reducing the false alarm rates when applied to analyte detection.
Developing representations for multimedia is an important and challenging problem with applications ranging from scene recognition, multi-media retrieval and personal life-logging systems to field robot navigation. In this dissertation, we present a new framework for feature extraction for challenging natural environment sounds. Proposed features outperform traditional spectral features on challenging environmental sound datasets. Several algorithms are proposed that perform supervised tasks such as recognition and tag annotation. Ensemble methods are proposed to improve the tag annotation process.
To facilitate the use of large datasets, fast implementations are developed for sparse coding, the key component in our algorithms. Several strategies to speed-up Orthogonal Matching Pursuit algorithm using CUDA kernel on a GPU are proposed. Implementations are also developed for a large scale image retrieval system. Image-based "exact search" and "visually similar search" using the image patch sparse codes are performed. Results demonstrate large speed-up over CPU implementations and good retrieval performance is also achieved.
To achieve a sensing diameter of 1-2 nanometers, the diatom shells were used as substrates to perform ion-channel reconstitution experiments. The immobilized diatom shell was functionalized using silane chemistry and lipid bilayer membranes were formed. Functionalization of the diatom shell surface improves bilayer formation probability from 1 out of 10 to 10 out of 10 as monitored by impedance spectroscopy. Self-insertion of outer membrane protein OmpF of E.Coli into the lipid membranes could be confirmed using single channel recordings, indicating that nano-BLMs had formed which allow for fully functional porin activity. The results indicate that biogenic silica nanoporous substrates can be simulated using a simplified two dimensional geometry to predict the current when a nanoparticle translocates through a single aperture. With their tiered three-dimensional structure, diatom shells can be used in to form nano-lipid bilayer membranes and can be used in ion-channel reconstitution experiments similar to synthetic nanoporous membranes.