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.
Displaying 61 - 70 of 70
Description
This research will explore the compositional approaches of Henry Cowell and John Cage to reveal piano techniques for the practice and performance of selected works. The discussion will focus on Henry Cowell’s Three Irish Legends and Six Ings, as well as John Cage’s The Perilous Night. An important contribution of Cowell was to further the use of tone clusters, applied in his Three Irish Legends by playing directly with the forearm, fists, and palm. Cowell’s Six Ings employ rhythmic experimentation, particularly in the first, second, and sixth pieces. He also uses tone color to portray specific programmatic features. John Cage greatly advanced the prepared piano from its earliest beginnings, as evidenced significantly in The Perilous Night. The present study will include advice on piano preparation, along with performance challenges and solutions.
ContributorsLiu, Xuan (Author) / Hamilton, Robert (Thesis advisor) / Campbell, Andrew (Committee member) / Rockmaker, Jody (Committee member) / Arizona State University (Publisher)
Created2020
Description
The field of cyber-defenses has played catch-up in the cat-and-mouse game of finding vulnerabilities followed by the invention of patches to defend against them. With the complexity and scale of modern-day software, it is difficult to ensure that all known vulnerabilities are patched; moreover, the attacker, with reconnaissance on their side, will eventually discover and leverage them. To take away the attacker's inherent advantage of reconnaissance, researchers have proposed the notion of proactive defenses such as Moving Target Defense (MTD) in cyber-security. In this thesis, I make three key contributions that help to improve the effectiveness of MTD.
First, I argue that naive movement strategies for MTD systems, designed based on intuition, are detrimental to both security and performance. To answer the question of how to move, I (1) model MTD as a leader-follower game and formally characterize the notion of optimal movement strategies, (2) leverage expert-curated public data and formal representation methods used in cyber-security to obtain parameters of the game, and (3) propose optimization methods to infer strategies at Strong Stackelberg Equilibrium, addressing issues pertaining to scalability and switching costs. Second, when one cannot readily obtain the parameters of the game-theoretic model but can interact with a system, I propose a novel multi-agent reinforcement learning approach that finds the optimal movement strategy. Third, I investigate the novel use of MTD in three domains-- cyber-deception, machine learning, and critical infrastructure networks. I show that the question of what to move poses non-trivial challenges in these domains. To address them, I propose methods for patch-set selection in the deployment of honey-patches, characterize the notion of differential immunity in deep neural networks, and develop optimization problems that guarantee differential immunity for dynamic sensor placement in power-networks.
First, I argue that naive movement strategies for MTD systems, designed based on intuition, are detrimental to both security and performance. To answer the question of how to move, I (1) model MTD as a leader-follower game and formally characterize the notion of optimal movement strategies, (2) leverage expert-curated public data and formal representation methods used in cyber-security to obtain parameters of the game, and (3) propose optimization methods to infer strategies at Strong Stackelberg Equilibrium, addressing issues pertaining to scalability and switching costs. Second, when one cannot readily obtain the parameters of the game-theoretic model but can interact with a system, I propose a novel multi-agent reinforcement learning approach that finds the optimal movement strategy. Third, I investigate the novel use of MTD in three domains-- cyber-deception, machine learning, and critical infrastructure networks. I show that the question of what to move poses non-trivial challenges in these domains. To address them, I propose methods for patch-set selection in the deployment of honey-patches, characterize the notion of differential immunity in deep neural networks, and develop optimization problems that guarantee differential immunity for dynamic sensor placement in power-networks.
ContributorsSengupta, Sailik (Author) / Kambhampati, Subbarao (Thesis advisor) / Bao, Tiffany (Youzhi) (Committee member) / Huang, Dijiang (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2020
Description
Pacific Suite (2016) is a four-movement work for solo piano composed by the author of this paper, Holly Kordahl, that incorporates elements of several musical idioms, including Impressionism, tintinnabuli (as in the music of Arvo Pärt), post-modernism, minimalism and improvisation. This Doctorate of Musical Arts project consists of a descriptive paper, analysis, score and recording. The piece features varying levels of performer independence and improvisation along with notated music. Each movement is named after a different environment of the Pacific Ocean: Great Barrier Reef, Mariana Trench, Sunlit Zone, and Bikini Atoll.
Pacific Suite is engaging to mature pianists and accessible to students. The score of Pacific Suite is a blank canvas in some ways; almost all dynamics, tempi, pedaling, and fingerings are to be determined by the performer. The first movement, Great Barrier Reef, presents different musical vignettes. The second movement, Mariana Trench, requires the performer to improvise extensively while following provided instructions. The third movement, Sunlit Zone, asks the performer to improvise on a theme of Debussy. The final movement, Bikini Atoll, illustrates events of nuclear testing at Bikini Atoll in the 1940s.
Pacific Suite is engaging to mature pianists and accessible to students. The score of Pacific Suite is a blank canvas in some ways; almost all dynamics, tempi, pedaling, and fingerings are to be determined by the performer. The first movement, Great Barrier Reef, presents different musical vignettes. The second movement, Mariana Trench, requires the performer to improvise extensively while following provided instructions. The third movement, Sunlit Zone, asks the performer to improvise on a theme of Debussy. The final movement, Bikini Atoll, illustrates events of nuclear testing at Bikini Atoll in the 1940s.
ContributorsKordahl, Holly (Author) / Meir, Baruch (Thesis advisor) / Bolanos, Gabriel (Committee member) / Campbell, Andrew (Committee member) / Hamilton, Robert (Committee member) / Ryan, Russell (Committee member) / Arizona State University (Publisher)
Created2020
Description
This research document focuses on rarely performed piano transcriptions. A total of 28 works are discussed. These works have high artistic value and should not be forgotten by pianists. Most of the transcribers are renowned pianists, such as Harold Bauer and Alfred Cortot, or composers themselves. Unfortunately, these works are seldom played in today's public concerts, or on online resources such as YouTube, Vimeo, or iTunes. Some people may think these works are neglected because the scores are hard to find, but they can be easily obtained online. Pianists around the world can access these scores in just a few minutes via the Internet.
In this research document, I discuss the transcriptions one by one. First, I introduce the background of the pieces, the composers, and the transcribers. Then, through comparison of the original pieces with the transcribed ones, I discuss the approaches of transcription and highlight the special features of each work. Finally, I recommend the concert occasions appropriate for the transcriptions based on their characteristics. I offer many musical examples from the works discussed. These excerpts should help the pianist to understand the style and technical difficulty, as well as to decide if the work meets their programming needs.
In this research document, I discuss the transcriptions one by one. First, I introduce the background of the pieces, the composers, and the transcribers. Then, through comparison of the original pieces with the transcribed ones, I discuss the approaches of transcription and highlight the special features of each work. Finally, I recommend the concert occasions appropriate for the transcriptions based on their characteristics. I offer many musical examples from the works discussed. These excerpts should help the pianist to understand the style and technical difficulty, as well as to decide if the work meets their programming needs.
ContributorsHuang, Kuang-Li (Author) / Meir, Baruch (Thesis advisor) / Campbell, Andrew (Committee member) / Hamilton, Robert (Committee member) / Holbrook, Amy (Committee member) / Arizona State University (Publisher)
Created2019
Description
Many existing applications of machine learning (ML) to cybersecurity are focused on detecting malicious activity already present in an enterprise. However, recent high-profile cyberattacks proved that certain threats could have been avoided. The speed of contemporary attacks along with the high costs of remediation incentivizes avoidance over response. Yet, avoidance implies the ability to predict - a notoriously difficult task due to high rates of false positives, difficulty in finding data that is indicative of future events, and the unexplainable results from machine learning algorithms.
In this dissertation, these challenges are addressed by presenting three artificial intelligence (AI) approaches to support prioritizing defense measures. The first two approaches leverage ML on cyberthreat intelligence data to predict if exploits are going to be used in the wild. The first work focuses on what data feeds are generated after vulnerability disclosures. The developed ML models outperform the current industry-standard method with F1 score more than doubled. Then, an approach to derive features about who generated the said data feeds is developed. The addition of these features increase recall by over 19% while maintaining precision. Finally, frequent itemset mining is combined with a variant of a probabilistic temporal logic framework to predict when attacks are likely to occur. In this approach, rules correlating malicious activity in the hacking community platforms with real-world cyberattacks are mined. They are then used in a deductive reasoning approach to generate predictions. The developed approach predicted unseen real-world attacks with an average increase in the value of F1 score by over 45%, compared to a baseline approach.
In this dissertation, these challenges are addressed by presenting three artificial intelligence (AI) approaches to support prioritizing defense measures. The first two approaches leverage ML on cyberthreat intelligence data to predict if exploits are going to be used in the wild. The first work focuses on what data feeds are generated after vulnerability disclosures. The developed ML models outperform the current industry-standard method with F1 score more than doubled. Then, an approach to derive features about who generated the said data feeds is developed. The addition of these features increase recall by over 19% while maintaining precision. Finally, frequent itemset mining is combined with a variant of a probabilistic temporal logic framework to predict when attacks are likely to occur. In this approach, rules correlating malicious activity in the hacking community platforms with real-world cyberattacks are mined. They are then used in a deductive reasoning approach to generate predictions. The developed approach predicted unseen real-world attacks with an average increase in the value of F1 score by over 45%, compared to a baseline approach.
ContributorsAlmukaynizi, Mohammed (Author) / Shakarian, Paulo (Thesis advisor) / Huang, Dijiang (Committee member) / Maciejewski, Ross (Committee member) / Simari, Gerardo I. (Committee member) / Arizona State University (Publisher)
Created2019
Description
Computer science education is an increasingly vital area of study with various challenges that increase the difficulty level for new students resulting in higher attrition rates. As part of an effort to resolve this issue, a new visual programming language environment was developed for this research, the Visual IoT and Robotics Programming Language Environment (VIPLE). VIPLE is based on computational thinking and flowchart, which reduces the needs of memorization of detailed syntax in text-based programming languages. VIPLE has been used at Arizona State University (ASU) in multiple years and sections of FSE100 as well as in universities worldwide. Another major issue with teaching large programming classes is the potential lack of qualified teaching assistants to grade and offer insight to a student’s programs at a level beyond output analysis.
In this dissertation, I propose a novel framework for performing semantic autograding, which analyzes student programs at a semantic level to help students learn with additional and systematic help. A general autograder is not practical for general programming languages, due to the flexibility of semantics. A practical autograder is possible in VIPLE, because of its simplified syntax and restricted options of semantics. The design of this autograder is based on the concept of theorem provers. To achieve this goal, I employ a modified version of Pi-Calculus to represent VIPLE programs and Hoare Logic to formalize program requirements. By building on the inference rules of Pi-Calculus and Hoare Logic, I am able to construct a theorem prover that can perform automated semantic analysis. Furthermore, building on this theorem prover enables me to develop a self-learning algorithm that can learn the conditions for a program’s correctness according to a given solution program.
In this dissertation, I propose a novel framework for performing semantic autograding, which analyzes student programs at a semantic level to help students learn with additional and systematic help. A general autograder is not practical for general programming languages, due to the flexibility of semantics. A practical autograder is possible in VIPLE, because of its simplified syntax and restricted options of semantics. The design of this autograder is based on the concept of theorem provers. To achieve this goal, I employ a modified version of Pi-Calculus to represent VIPLE programs and Hoare Logic to formalize program requirements. By building on the inference rules of Pi-Calculus and Hoare Logic, I am able to construct a theorem prover that can perform automated semantic analysis. Furthermore, building on this theorem prover enables me to develop a self-learning algorithm that can learn the conditions for a program’s correctness according to a given solution program.
ContributorsDe Luca, Gennaro (Author) / Chen, Yinong (Thesis advisor) / Liu, Huan (Thesis advisor) / Hsiao, Sharon (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2020
Description
The purpose of an election is for the voice of the voters to be heard. All the participants in an election must be able to trust that the result of an election is actually the opinion of the people, unaltered by anything or anyone that may be trying to sway the vote. In the voting process, any "black boxes" or secrets can lead to mistrust in the system. In this thesis, an approach is developed for an electronic voting framework that is transparent, auditable, and scalable, making it trustworthy and usable for a wide-scale election. Based on my analysis, linkable ring signatures are utilized in order to preserve voter privacy while ensuring that a corrupt authenticating authority could not sway the vote. A hierarchical blockchain framework is presented to make ring signatures a viable signature scheme even when working with large populations. The solution is evaluated for compliance with secure voting requirements and scalability.
ContributorsMarple, Sam (Author) / Yau, Sik-Sang (Thesis advisor) / Huang, Dijiang (Committee member) / Trieu, Ni (Committee member) / Arizona State University (Publisher)
Created2021
Description
ABSTRACT
As a composer, Chou Wen-Chung (1923-2019) was a learner and inheritor of Chinese traditional music culture and was committed to carrying it forward. As a native of China who had his primary musical training in the West, Chou Wen-Chung was one of the first Chinese composers to make his mark on Western music. He successfully combined Western elements and Chinese tradition in his music. Chou Wen-Chung was one of the few prominent East Asian composers known in the Western musical world, and his music therefore has had a strong influence on other Chinese composers.
In order to understand more clearly his music, I analyzed his chamber work: Yü Ko. This piece was composed in 1965 for 9 instruments: Violin, Alto Flute, English Horn, Bass Clarinet, 2 Trombones, 2 Percussion and Piano. Inspired by the ancient Chinese musical instrument the Qin (also called guqin, or “ancient qin”), which is a plucked seven-string instrument, Chou Wen-Chung composed Yü Ko. Literally meaning “fisherman’s song,” this work was composed originally for the Qin, based on a melody composed by Mao Min-Zhong who was a very noted scholar and Qin player of the late Southern Song dynasty (C.E.1127-1276).
This paper provides Chou Wen-Chung’s biography, compositional styles and developments. It lists and explains the most common Chinese traditional cultural elements which he used in his compositions. In particular, it introduces the Qin in detail from the external structure, performance techniques, sound characteristics, the tablature notation, and compositional methods.
This document also includes a detailed analysis of Yü Ko in terms of the orchestration, pitch, tonal material, structure and tempo, dynamic and musical materials, and explains Chou Wen-Chung’s imitation of the Qin as well as the influence of Western music shown in this piece.
As a composer, Chou Wen-Chung (1923-2019) was a learner and inheritor of Chinese traditional music culture and was committed to carrying it forward. As a native of China who had his primary musical training in the West, Chou Wen-Chung was one of the first Chinese composers to make his mark on Western music. He successfully combined Western elements and Chinese tradition in his music. Chou Wen-Chung was one of the few prominent East Asian composers known in the Western musical world, and his music therefore has had a strong influence on other Chinese composers.
In order to understand more clearly his music, I analyzed his chamber work: Yü Ko. This piece was composed in 1965 for 9 instruments: Violin, Alto Flute, English Horn, Bass Clarinet, 2 Trombones, 2 Percussion and Piano. Inspired by the ancient Chinese musical instrument the Qin (also called guqin, or “ancient qin”), which is a plucked seven-string instrument, Chou Wen-Chung composed Yü Ko. Literally meaning “fisherman’s song,” this work was composed originally for the Qin, based on a melody composed by Mao Min-Zhong who was a very noted scholar and Qin player of the late Southern Song dynasty (C.E.1127-1276).
This paper provides Chou Wen-Chung’s biography, compositional styles and developments. It lists and explains the most common Chinese traditional cultural elements which he used in his compositions. In particular, it introduces the Qin in detail from the external structure, performance techniques, sound characteristics, the tablature notation, and compositional methods.
This document also includes a detailed analysis of Yü Ko in terms of the orchestration, pitch, tonal material, structure and tempo, dynamic and musical materials, and explains Chou Wen-Chung’s imitation of the Qin as well as the influence of Western music shown in this piece.
ContributorsSong, Yiqian (Author) / Ryan, Russell (Thesis advisor) / Campbell, Andrew (Committee member) / Solís, Ted (Committee member) / Arizona State University (Publisher)
Created2020
Description
Machine learning tutorials often employ an application and runtime specific solution for a given problem in which users are expected to have a broad understanding of data analysis and software programming. This thesis focuses on designing and implementing a new, hands-on approach to teaching machine learning by streamlining the process of generating Inertial Movement Unit (IMU) data from multirotor flight sessions, training a linear classifier, and applying said classifier to solve Multi-rotor Activity Recognition (MAR) problems in an online lab setting. MAR labs leverage cloud computing and data storage technologies to host a versatile environment capable of logging, orchestrating, and visualizing the solution for an MAR problem through a user interface. MAR labs extends Arizona State University’s Visual IoT/Robotics Programming Language Environment (VIPLE) as a control platform for multi-rotors used in data collection. VIPLE is a platform developed for teaching computational thinking, visual programming, Internet of Things (IoT) and robotics application development. As a part of this education platform, this work also develops a 3D simulator capable of simulating the programmable behaviors of a robot within a maze environment and builds a physical quadrotor for use in MAR lab experiments.
ContributorsDe La Rosa, Matthew Lee (Author) / Chen, Yinong (Thesis advisor) / Collofello, James (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2018
Description
The Sonata for Cello and Piano (1915) was one of the last three sonatas written by Claude Debussy (1862–1918). When Debussy composed the sonata, France was involved in World War I and Debussy was influenced by political dogmas that sought to advance nationalism as well as the use of French traditions in musical compositions. By discussing the political impact of World War I on French music, this paper will place the Sonata in a context that strengthens the understanding of the work.
Debussy, who participated in the political project of seeking out tradition as the protector of French culture, also presents his understanding of what French tradition is in this sonata. An analytical description of the structure, thematic materials, harmonies and intervallic relationships of the Sonata reveals Debussy’s approach of combining the elements that he observed from his French predecessors, as well as his own innovations in the work as he negotiated musical world that was controlled by political dogma
Debussy, who participated in the political project of seeking out tradition as the protector of French culture, also presents his understanding of what French tradition is in this sonata. An analytical description of the structure, thematic materials, harmonies and intervallic relationships of the Sonata reveals Debussy’s approach of combining the elements that he observed from his French predecessors, as well as his own innovations in the work as he negotiated musical world that was controlled by political dogma
ContributorsSong, Peipei (Author) / Ryan, Russell (Thesis advisor) / Campbell, Andrew (Committee member) / Feisst, Sabine (Committee member) / Landschoot, Thomas (Committee member) / Arizona State University (Publisher)
Created2016