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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- Creators: Barrett, The Honors College
Description
The belt component of a unique and novel wireless spinal cord stimulator (SCS) system was conceived, designed, made, and verified. This thesis details and documents all work from inception through preliminary verification and includes recommendations for future work. The purpose, scope, and objectives of the design and the thesis are introduced. Background literature is presented to provide context for the wireless SCS system as well as the belt component of the system. The product development process used to design the product is outlined. Requirements and constraints are determined from customer needs. Design options are considered and the best concept is selected. The design is made, optimized, and verified to meet the requirements. Future work for this design, outside the scope of this thesis, is discussed. Recommendations and conclusions following completion of the design are included as well.
ContributorsSimeunovic, Andrej (Author) / Zhu, Haolin (Thesis director) / Bakkaloglu, Bertan (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
Description
NGExtract 2 is a complete transistor (MOSFET) parameter extraction solution based upon the original computer program NGExtract by Rahul Shringarpure written in February 2007. NGExtract 2 is written in Java and based around the circuit simulator NGSpice. The goal of the program is to be used to produce accurate transistor models based around real-world transistor data. The program contains numerous improvements to the original program:
• Completely rewritten with performance and usability in mind
• Cross-Platform vs. Linux Only
• Simple installation procedure vs. compilation and manual library configuration
• Self-contained, single file runtime
• Particle Swarm Optimization routine
NGExtract 2 works by plotting the Ids vs. Vds and Ids vs. Vgs curves of a simulation model and the measured, real-world data. The user can adjust model parameters and re-simulate to attempt to match the curves. The included Particle Swarm Optimization routine attempts to automate this process by iteratively attempting to improve a solution by measuring its sum-squared error against the real-world data that the user has provided.
• Completely rewritten with performance and usability in mind
• Cross-Platform vs. Linux Only
• Simple installation procedure vs. compilation and manual library configuration
• Self-contained, single file runtime
• Particle Swarm Optimization routine
NGExtract 2 works by plotting the Ids vs. Vds and Ids vs. Vgs curves of a simulation model and the measured, real-world data. The user can adjust model parameters and re-simulate to attempt to match the curves. The included Particle Swarm Optimization routine attempts to automate this process by iteratively attempting to improve a solution by measuring its sum-squared error against the real-world data that the user has provided.
ContributorsVetrano, Michael Thomas (Author) / Allee, David (Thesis director) / Gorur, Ravi (Committee member) / Bakkaloglu, Bertan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
This report outlines the current methods and instrumentation used for diabetes monitoring and detection, and evaluates the problems that these methods face. Additionally, it will present an approach to remedy these problems. The purpose of this project is to create a potentiostat that is capable of controlling a diabetes meter that monitors multiple biological markers simultaneously. Glucose is the most commonly measured biomarker for diabetes. However, it provides only a limited amount of information. In order to give the user of the meter more information about the progression of his or her disease, the concentrations of several different biological markers for diabetes may be measured using a system that operates in a similar fashion to blood glucose meters. The potentiostat provides an input voltage into the electrode sensor and receives the current from the sensor as the output. From this information, the impedance may be calculated. The concentrations of each of the biomarkers in the blood sample can then be determined. In an effort to increase sensitivity, the diabetes meter forgoes the use of amperometric i-t in favor of the electrochemical impedance spectroscopy technique. A three-electrode electrochemical sensor is used with the meter. In order to perform simultaneous and rapid testing of biomarker concentration, a single multisine input wave is generated using a hardware implementation of a summing amplifier and waveform generators.
ContributorsWu, Diane Zhang (Author) / LaBelle, Jeffrey (Thesis director) / Bakkaloglu, Bertan (Committee member) / Spano, Mark (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2013-05