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Description
With the substantial development of intelligent robots, human-robot interaction (HRI) has become ubiquitous in applications such as collaborative manufacturing, surgical robotic operations, and autonomous driving. In all these applications, a human behavior model, which can provide predictions of human actions, is a helpful reference that helps robots to achieve intelligent

With the substantial development of intelligent robots, human-robot interaction (HRI) has become ubiquitous in applications such as collaborative manufacturing, surgical robotic operations, and autonomous driving. In all these applications, a human behavior model, which can provide predictions of human actions, is a helpful reference that helps robots to achieve intelligent interaction with humans. The requirement elicits an essential problem of how to properly model human behavior, especially when individuals are interacting or cooperating with each other. The major objective of this thesis is to utilize the human intention decoding method to help robots enhance their performance while interacting with humans. Preliminary work on integrating human intention estimation with an HRI scenario is shown to demonstrate the benefit. In order to achieve this goal, the research topic is divided into three phases. First, a novel method of an online measure of the human's reliance on the robot, which can be estimated through the intention decoding process from human actions,is described. An experiment that requires human participants to complete an object-moving task with a robot manipulator was conducted under different conditions of distractions. A relationship is discovered between human intention and trust while participants performed a familiar task with no distraction. This finding suggests a relationship between the psychological construct of trust and joint physical coordination, which bridges the human's action to its mental states. Then, a novel human collaborative dynamic model is introduced based on game theory and bounded rationality, which is a novel method to describe human dyadic behavior with the aforementioned theories. The mutual intention decoding process was also considered to inform this model. Through this model, the connection between the mental states of the individuals to their cooperative actions is indicated. A haptic interface is developed with a virtual environment and the experiments are conducted with 30 human subjects. The result suggests the existence of mutual intention decoding during the human dyadic cooperative behaviors. Last, the empirical results show that allowing agents to have empathy in inference, which lets the agents understand that others might have a false understanding of their intentions, can help to achieve correct intention inference. It has been verified that knowledge about vehicle dynamics was also important to correctly infer intentions. A new courteous policy is proposed that bounded the courteous motion using its inferred set of equilibrium motions. A simulation, which is set to reproduce an intersection passing case between an autonomous car and a human driving car, is conducted to demonstrate the benefit of the novel courteous control policy.
ContributorsWang, Yiwei (Author) / Zhang, Wenlong (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Ren, Yi (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2021
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Description
The increasing concentrations of greenhouse gases into the atmosphere call for urgent measures to use non-fossil feedstock for fuels and chemicals. Synthesis gas (or syngas) is a mixture of three gases: hydrogen (H2), carbon monoxide (CO), and carbon dioxide (CO2). Syngas already is widely used as a

The increasing concentrations of greenhouse gases into the atmosphere call for urgent measures to use non-fossil feedstock for fuels and chemicals. Synthesis gas (or syngas) is a mixture of three gases: hydrogen (H2), carbon monoxide (CO), and carbon dioxide (CO2). Syngas already is widely used as a non-fossil fuel and a building block for a variety of chemicals using the Fischer-Tropsch process. Recently, syngas fermentation has attracted attention as a more sustainable way for the conversion of syngas to chemicals, since its biocatalysts are self-generating, are resilient, and can utilize a wide range of syngas compositions. However, syngas fermentation has technical and economic limitations. This dissertation, by contributing to the understanding of syngas fermentation, helps to overcome the limitations. A bibliometric analysis showed the topic’s landscape and identified that mass transfer is the biggest challenge for the process. One means to improve syngas mass transfer is to use the membrane biofilm reactor, or MBfR, to deliver syngas to the microorganisms. MBfR experiments delivering pure H2 demonstrated that the H2:IC ratio (IC is inorganic carbon) controlled the overall production rate of organic compounds and their carbon-chain length. Organic chemicals up to eight carbons could be produced with a high H2:IC ratio. A novel asymmetric membrane dramatically improved mass transfer rates for all syngas components, and its low selectivity among them made it ideal for high-rate syngas fermentation. MBfR experiments using syngas and the asymmetric membrane, as well as a conventional symmetric membrane, confirmed that the key parameter for generating long-chain products was a high H2:IC ratio. The fast mass transfer rate of the asymmetric membrane allowed a very high areal production rate of acetate: 253 g.m-2.d-1, the highest reported to date. Since the membrane delivered H2 and C from the syngas feed, the relatively low selectivity of the asymmetric membrane favored acetogenesis over microbial chain elongation. A techno-economic analysis of the MBfR showed that the cost to produce acetate was less than its market price. All results presented in this dissertation support the potential of syngas fermentation using the MBfR as a means to produce commodity chemicals and biofuels from syngas.
ContributorsCalvo Martinez, Diana Carolina (Author) / Rittmann, Bruce E (Thesis advisor) / Torres, César I (Thesis advisor) / Kralmajnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Within a positive youth development framework, Lerner and colleagues posited that youth and young adults are societal assets that support the pillars of democracy and incite community contribution through the development of individual character strengths. Strengths might include hope and civic attitudes, which researchers have linked to numerous positive outcomes;

Within a positive youth development framework, Lerner and colleagues posited that youth and young adults are societal assets that support the pillars of democracy and incite community contribution through the development of individual character strengths. Strengths might include hope and civic attitudes, which researchers have linked to numerous positive outcomes; however, connections to civic behaviors are largely unknown. Developmentally, shifting identities, excitement about the future, and an introduction into formal citizenship within U.S. society characterize the emerging adulthood period. Emerging adulthood is also characterized by burgeoning relationships and service opportunities, particularly on college campuses. These factors make emerging adulthood a prime context in which to investigate the aims of the current study, which centered on investigation of the development of hope and civic attitudes, and how each contributed to civic engagement including interpersonal prosocial behavior, community volunteering, and political behaviors. Effortful control was hypothesized to play a role in relations as an intrapersonal factor that implicated relations between hope and civic attitudes and outcomes, and was therefore included as a moderator. Sample consisted of 217 emerging adults (~ 67% female, 58% White, 30% Pell-grant eligible, 19-20 years old) across three time points at a major university in the southwest U.S. from spring 2019 to spring 2020. Path models, structural equation models, and moderation analyses evidenced direct relations between hope and interpersonal prosocial behavior. Civic attitudes directly related to community volunteering and political engagement. Transactional relations between hope and civic engagement were not apparent. Similarly, moderation analyses showed no interactive effects between hope and civic attitudes and effortful control on study outcomes. Findings evidenced stability in hope and civic attitudes across early emerging adulthood and invited future work investigating the development of each in early adolescence and later emerging adulthood. Future interventions might prioritize the development of hope in efforts to increase interpersonal prosociality and civic attitudes to increase volunteering and political engagement among emerging adults, where civic engagement has been historically low. Overall, findings supported hope and civic attitudes as hallmarks of positive youth development with the potential to uniquely contribute to community enhancement in emerging adulthood.
ContributorsFraser, Ashley Michelle (Author) / Spinrad, Tracy L (Thesis advisor) / Bryce, Crystal I (Committee member) / Eisenberg, Nancy (Committee member) / Morris, Stacy L (Committee member) / Arizona State University (Publisher)
Created2021
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Description
The southwestern United States is an ecologically, climatologically, and topographically diverse geographical region. As a result, it has been difficult to develop accurate assessments and instructional pedagogy for defining and demonstrating climate sensitivity and change at a more local level. To address this problem, this dissertation is divided into two

The southwestern United States is an ecologically, climatologically, and topographically diverse geographical region. As a result, it has been difficult to develop accurate assessments and instructional pedagogy for defining and demonstrating climate sensitivity and change at a more local level. To address this problem, this dissertation is divided into two distinct sections involving climate data collection/analysis and geography education using interactive geovisualization video games (iGEOs). The first two papers analyze new climate observations in Joshua Tree National Park. The first paper examines the variability in accuracy of climate reanalysis and interpolation methods compared to field observations in Joshua Tree National Park and the Tucson Metropolitan Area. This study found that other than PRISM interpolation data, reanalysis techniques performed better in a region with a more extensive climate network. The second paper developed a climate regionalization zone separating the Mojave and Sonoran Deserts within Joshua Tree National Park using principal component analysis. This study used monthly temperature and precipitation observations, as well as seasonal climate trends. The final two papers describe and analyze the implementation of virtual interactive geovisualization video games (iGEOs) used to instruct geographical concepts in an introductory physical geography course at Arizona State University. The first paper examines the preliminary implementation of an iGEO in the San Francisco Peaks of northern Arizona, identifying student support for the games, but with caveats related to the technical shortcomings of the game design, and noticeable differences based on academic major. The second paper examines the changing experiences and challenges encountered by both students and instructors in an iGEO centered introductory geography course during the COVID-19 pandemic. This study found that, while students were impacted by the pandemic, all student groups had sufficient extensive and intensive learning materials to ensure a positive and successful lab experience. Overall, the significance of these four papers demonstrates that new applications of climate observations and geography pedagogy can effectively describe local climate sensitivity and instruct geographic concepts in the mountainous Southwest.
ContributorsHeintzman, Ryan Joseph (Author) / Cerveny, Randall S (Thesis advisor) / Dorn, Ronald I (Thesis advisor) / Balling Jr, Robert C (Committee member) / Selover, Nancy (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Pulitzer Prize-winning composer Michael Colgrass wrote Tales of power: A Musical Drama for Solo Piano on the Writings of Carlos Castaneda in 1980. However, since the work’s premiere it has been overlooked, receiving little attention from pianists. This neglect is perhaps due, in part, to the absence of circulated recordings

Pulitzer Prize-winning composer Michael Colgrass wrote Tales of power: A Musical Drama for Solo Piano on the Writings of Carlos Castaneda in 1980. However, since the work’s premiere it has been overlooked, receiving little attention from pianists. This neglect is perhaps due, in part, to the absence of circulated recordings and writings. The present study includes the author’s recorded performance, found online at https://youtu.be/GqzMjgaSIDc. Because Tales of Power is a programmatic work about Carlos Castaneda’s study with Don Juan, an Indian sorcerer from Mexico, the author has inserted the score’s written program indications in the recording so that listeners may follow the narrative. This performance guide includes a concise biography of Colgrass, a review of the composer’s major works and general compositional styles, observations on the program and structure, insights regarding thematic transformation and recurring motives, and performance recommendations for accommodating troublesome sections. The author hopes that Tales of Power can be revived in concert performance and become part of the programmatic piano repertoire in the near future.
ContributorsLi, Aoshuang (Author) / Hamilton, Robert (Thesis advisor) / Rockmaker, Jody Rockmaker (Committee member) / Ryan, Russell (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Drinking water quality violations are widespread in the United States and elsewhere in the world. More than half of Americans are not confident in the safety of their tap water, especially after the 2014 Flint, Michigan water crisis. Other than accidental contamination events, stagnation is a major cause of water

Drinking water quality violations are widespread in the United States and elsewhere in the world. More than half of Americans are not confident in the safety of their tap water, especially after the 2014 Flint, Michigan water crisis. Other than accidental contamination events, stagnation is a major cause of water quality degradation. Thus, there is a pressing need to build a real-time control system that can make control decisions quickly and proactively so that the quality of water can be maintained at all times. However, towards this end, modeling the dynamics of water distribution systems are very challenging due to the complex fluid dynamics and chemical reactions in the system. This challenge needs to be addressed before moving on to modeling the optimal control problem. The research in this dissertation leverages statistical machine learning approaches in approximating the complex water system dynamics and then develops different optimization models for proactive and real-time water quality control. This research focuses on two effective ways to maintain water quality, flushing of taps and injection of chlorine or other disinfectants; both of these actions decrease the equivalent “water age”, a useful proxy for water quality related to bacteria growth. This research first develops linear predictive models for water quality and subsequently linear programming optimization models for proactive water age control via flushing. The second part of the research considers both flushing and disinfectant injections in the control problem and develops mixed integer quadratically constrained optimization models for controlling water age. Different control strategies for disinfectant injections are also evaluated: binary on-off injections and continuous injections. In the third part of the research, water demand is assumed to be uncertain and stochastic. The developed approach to control the system relates to learning the optimal real-time flushing decisions by combing reinforced temporal-difference learning approaches with linear value function approximation for solving approximately the underlying Markov decision processes. Computational results on widely used simulation models demonstrates the developed control systems were indeed effective for water quality control with known demands as well as when demands are uncertain and stochastic.
ContributorsLi, Xiushuang (Author) / Mirchandani, Pitu (Thesis advisor) / Boyer, Treavor (Committee member) / Ju, Feng (Committee member) / Pedrielli, Giulia (Committee member) / Arizona State University (Publisher)
Created2021
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Description
This dissertation consists of three essays on the task approach to labor markets. In the first chapter, I document that since 2000 the polarization of wages in the U.S. labor market stopped, as the wages of non-routine manual occupations fell in relative and absolute terms. I analyze the end of

This dissertation consists of three essays on the task approach to labor markets. In the first chapter, I document that since 2000 the polarization of wages in the U.S. labor market stopped, as the wages of non-routine manual occupations fell in relative and absolute terms. I analyze the end of wage polarization through the lens of a dynamic general equilibrium model with occupation-biased technical change, human capital accumulation, and occupational mobility. I show that wage polarization ended because workers in non-routine manual occupations had lower initial human capital and lower human capital accumulation over time, and because after 2000 mobility across occupations fell, which magnified the differences in human capital accumulation across occupations. The second chapter estimates the effect of the import competition from China on the intensity of tasks performed by workers within U.S. manufacturing establishments between 2002 and 2017. I measure the changes in the intensity of these tasks by linking information on occupational employment from the Occupational Employment Statistics to the occupational characteristics from the Occupational Information Network (O*NET). I find that this “China shock” led establishments to significantly decrease the intensity of cognitive and interpersonal tasks, and to increase the intensity of manual and routine tasks. These estimations are consistent with US establishments reallocating employment to become more similar to their Chinese competitors and have important implications for the design of public policies. The third chapter explores the importance of changes in the intensity of tasks performed by workers to explain the evolution of wages. Despite changes in the workplace, the literature is based on the questionable assumption that the intensity of tasks remains constant over time. I harmonize and compare over time the intensity of non-routine cognitive, non-routine manual, interpersonal, and routine tasks in the Dictionary of Occupation Title (DOT) and the O*NET. I find the new fact that a sizable part of wage changes is due to increases in the return and the intensity of cognitive tasks. I show that this fact has implications for three well-documented wage trends during the last decades: wage polarization, increasing college premium, decreasing gender-wage gap.
ContributorsGarcia-Couto, Santiago (Author) / Herrendorf, Berthold (Thesis advisor) / Ventura, Gustavo (Committee member) / Ferraro, Domenico (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Building-integrated carbon-capture (BICC) is an envisioned mechanism capable of absorbing carbon dioxide (CO2) from the air to be stored and then converted into useful carbon-based materials without negatively impacting the environment. This dissertation builds on the authors' previous work, in which building façades were treated as artificial leaves capable of

Building-integrated carbon-capture (BICC) is an envisioned mechanism capable of absorbing carbon dioxide (CO2) from the air to be stored and then converted into useful carbon-based materials without negatively impacting the environment. This dissertation builds on the authors' previous work, in which building façades were treated as artificial leaves capable of providing shade to lower solar heat gain, while simultaneously capturing CO2 through the air filters attached to the building façades by attempting a different approach capable of capturing CO2 within buildings. This dissertation presents the author’s work on BICC, where buildings are envisioned as CO2 reservoirs or vacuums, into which mechanical systems introduce fresh air, and through human activities, the air within the building becomes enriched with CO2 before being pushed out back to the outer environment. The design of a carbon-capture mechanism will take advantage of the ventilation side of existing HVAC systems, through which BICC captures CO2 from the exhaust-enriched CO2 air. BICC will utilize existing opportunities and components within buildings represented in the high CO2 concentration in buildings, ventilation guidelines, mechanical equipment represented in air handling unit and air duct network, in addition to natural gas grid connectivity. BICC will capture CO2 through buildings' mechanical system, and the captured CO2 would then be converted into renewable methane to be injected into the existing natural gas pipeline network. This dissertation will investigate the potential of BICC to offset carbon emissions from multiple commercial building types and will present a utilization strategy for the captured carbon.
ContributorsBen Salamah, Fahad (Author) / Bryan, Harvey (Thesis advisor) / Lackner, Klaus (Committee member) / Reddy, T Agami (Committee member) / Arizona State University (Publisher)
Created2021
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Description
The proliferation of semantic data in the form of RDF (Resource Description Framework) triples demands an efficient, scalable, and distributed storage along with a highly available and fault-tolerant parallel processing strategy. There are three open issues with distributed RDF data management systems that are not well addressed altogether in existing

The proliferation of semantic data in the form of RDF (Resource Description Framework) triples demands an efficient, scalable, and distributed storage along with a highly available and fault-tolerant parallel processing strategy. There are three open issues with distributed RDF data management systems that are not well addressed altogether in existing work. First is the querying efficiency, second is that solutions are optimized for certain types of query patterns and don’t necessarily work well for all types, and third is concerned with reducing pre-processing cost. Therefore, the rapid growth of RDF data raises the need for an efficient partitioning strategy over distributed data management systems to improve SPARQL (SPARQL Protocol and RDF Query Language) query performance regardless of its pattern shape with minimized pre-processing overhead. In this context, the first contribution of this work is a distributed RDF data partitioning schema called 3CStore that extends the existing VP (Vertical Partitioning) approach by using a subset of triples from the VP tables based on different join correlations. This approach speeds up queries at the cost of additional pre-processing overhead. To solve this, a relational partitioning schema called VPExp was developed by splitting predicates based on explicit type information of objects. This approach gains a significant query performance only for the specific type of query where the object is bound to a value for a particular predicate. To get efficient query performance on a wide range of query patterns, an improved solution is proposed by extending the existing Property Table approach to Subset-Property Table and combined with the VP approach. Further investigation on distributed RDF processing and querying systems based on typical use cases led to a novel relational partitioning schema called PTP (Property Table Partitioning) that further partitions the whole Property Table into the number of unique properties to minimize query input size and join operations during query evaluation. Finally, an RDF data management system based on the SPARQL-over-SQL approach called S3QLRDF is developed that generates the optimal query execution plan using statistics of PTP tables to provide efficient SPARQL query processing on a distributed system.
ContributorsHassan, P M Mahmudul Mahmudul (Author) / Bansal, Srividya (Thesis advisor) / Bansal, Ajay (Committee member) / Davulcu, Hasan (Committee member) / Sarwat Abdelghany Aly Elsayed, Mohamed (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Technology and society co-exist, influencing each other simultaneously and iteratively, in ways that are sufficiently interdependent that it can be hard to see where one ends and the other begins. A set of sociotechnical relations exist between and across society and technologies that structure the ways that people live and

Technology and society co-exist, influencing each other simultaneously and iteratively, in ways that are sufficiently interdependent that it can be hard to see where one ends and the other begins. A set of sociotechnical relations exist between and across society and technologies that structure the ways that people live and work. What happens to sociotechnical relations when technologies are introduced or changed? In this dissertation, I argue that key parts of the processes that link technological and social change occur in a liminal space between the invention of new technologies and their widespread adoption and integration in society. In this space, engineers, businesses, and users of new technologies imagine, explore, develop, and test new ways of weaving together technology and society in novel sociotechnical arrangements. I call this space between invention and adoption a testbed, which I theorize as an early phase of technological deployment where outcomes are explored and tested, and sociotechnical assemblages are imagined, assembled, evaluated, and stabilized. I argue that the testbed, which is often delimited in both time and location, should be understood, interrogated, and governed appropriately to anticipate and examine the possibilities of social disruption inherent in technological change and to design the relationships between technology and society to improve sociotechnical outcomes. To understand the testbed, I engage in a case study of the Arizona public autonomous vehicle testbed, leveraging a multi-method approach that includes public observations, interviews, a survey, and content analyses. Through this work, I analyze diverse aspects of the testbed and articulate how the work of testbed actors imagines, assembles, tests, and stabilizes sociotechnical assemblages and futures. The dissertation builds on the insights gained from this investigation to evaluate the testbed and develop recommendations about assessing the space between technology invention and widespread adoption. Ultimately, this dissertation concludes that testbeds are key places where futures get made and so should be given greater attention by theorists of innovation and by societies confronting the societal and ethical challenges posed by new technologies.
ContributorsRadatz, Alecia (Author) / Miller, Clark (Thesis advisor) / Wetmore, Jameson (Committee member) / Richter, Jennifer (Committee member) / Arizona State University (Publisher)
Created2021