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This paper documents a study of the relationship between heads up display (HUDs) customization and player performance. Additional measures capture satisfaction and prior gaming experience. The goal of this study was to develop a framework on which future Human Systems Engineering studies could create games that are tailor made to

This paper documents a study of the relationship between heads up display (HUDs) customization and player performance. Additional measures capture satisfaction and prior gaming experience. The goal of this study was to develop a framework on which future Human Systems Engineering studies could create games that are tailor made to examine a given area of interest. This study utilized a two-by-two design, where participants play a two-dimensional (2D) platformer game with a mechanic that incentivizes attention to the HUD. This study successfully developed a framework and was moderately successful in uncovering limitations and demonstrating areas for improvement in follow-on studies. Specifically, this study illuminated issues with the low amount of usable data caused by design issues, participant apathy, and reliance on self-reporting data collection. Extensions of this study can utilize this framework and should look to recruit beyond crowdsourcing platforms, collect more diverse data, reduce participant effort, and address other considerations that were found during execution.
ContributorsWallace, Xavier Guillermo (Author) / Roscoe, Rod (Thesis advisor) / Mara, Andrew (Committee member) / Cooke, Nancy (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Police excessive force, unlawful stops and searches, false arrests, and other forms of misconduct remain significant issues in American law enforcement. Abuses of power by even a few police officers erode public trust, reduce the legitimacy of law enforcement, and expose individual officers and law enforcement agencies to criminal and

Police excessive force, unlawful stops and searches, false arrests, and other forms of misconduct remain significant issues in American law enforcement. Abuses of power by even a few police officers erode public trust, reduce the legitimacy of law enforcement, and expose individual officers and law enforcement agencies to criminal and civil liability. When misconduct occurs, inadequate police leadership and supervision are often cited as contributing causes. First-line supervisors have direct, positional authority to influence the behavior of officers they lead, yet little is known about what actions first-line supervisors are expected to take to prevent misconduct. Federal consent decrees have been a promising area of police reform knowledge for researchers and practitioners. While these documents enumerate dozens of police reform measures in multiple subject areas, the role of the first-line supervisor remains disparate and unclear, ultimately hampering the effectiveness of first-line supervisors in operationalizing the reforms prescribed by these documents. The aim of this study was to develop a conceptual model that enhances understanding of actions police first-line supervisors are expected to take to prevent officer misconduct. A qualitative content analysis of federal consent decrees led to the development of six themes and a conceptual model that describe expected first-line supervisor behavior. This paper contributes to the body of knowledge about police leadership in the context of misconduct prevention and consent decree reform. It proposes a conceptual model helpful to police practitioners seeking to better define the role of first-line supervisors in an unpredictable, complex work environment that leaves little room for error.
ContributorsSmith, Benjamin (Author) / Veach, Paula (Thesis advisor) / Kirsch, Robert (Committee member) / Wallace, Lillian M (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Additive manufacturing consists of successive fabrication of materials layer upon layer to manufacture three-dimensional items. Several key problems such as poor quality of finished products and excessive operational costs are yet to be addressed before it becomes widely applicable in the industry. Retroactive/offline actions such as post-manufacturing inspections for

Additive manufacturing consists of successive fabrication of materials layer upon layer to manufacture three-dimensional items. Several key problems such as poor quality of finished products and excessive operational costs are yet to be addressed before it becomes widely applicable in the industry. Retroactive/offline actions such as post-manufacturing inspections for defect detection in finished products are not only extremely expensive and ineffective but are also incapable of issuing corrective action signals during the building span. In-situ monitoring and optimal control methods, on the other hand, can provide viable alternatives to aid with the online detection of anomalies and control the process. Nevertheless, the complexity of process assumptions, unique structure of collected data, and high-frequency data acquisition rate severely deteriorates the performance of traditional and parametric control and process monitoring approaches. Out of diverse categories of additive manufacturing, Large-Scale Additive Manufacturing (LSAM) by material extrusion and Laser Powder Bed Fusion (LPBF) suffer the most due to their more advanced technologies and are therefore the subjects of study in this work. In LSAM, the geometry of large parts can impact the heat dissipation and lead to large thermal gradients between distance locations on the surface. The surface's temperature profile is captured by an infrared thermal camera and translated to a non-linear regression model to formulate the surface cooling dynamics. The surface temperature prediction methodology is then combined into an optimization model with probabilistic constraints for real-time layer time and material flow control. On-axis optical high-speed cameras can capture streams of melt pool images of laser-powder interaction in real-time during the process. Model-agnostic deep learning methods offer a great deal of flexibility when facing such unstructured big data and thus are appealing alternatives to their physical-related and regression-based modeling counterparts. A configuration of Convolutional Long-Short Term Memory (ConvLSTM) auto-encoder is proposed to learn a deep spatio-temporal representation from sequences of melt pool images collected from experimental builds. The unfolded bottleneck tensors are then further mined to construct a high accuracy and low false alarm rate anomaly detection and monitoring procedure.
ContributorsFathizadan, Sepehr (Author) / Ju, Feng (Thesis advisor) / Wu, Teresa (Committee member) / Lu, Yan (Committee member) / Iquebal, Ashif (Committee member) / Arizona State University (Publisher)
Created2022
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Description
This study investigated the difference in biofilm growth on pristine and aged polypropylene microplastics exposed to Tempe Town Lake water for 8 weeks. The research question here is, does the aging of microplastic (MPs) change the biofilm formation rate and composition of the biofilm in comparison with the pristine MPs.

This study investigated the difference in biofilm growth on pristine and aged polypropylene microplastics exposed to Tempe Town Lake water for 8 weeks. The research question here is, does the aging of microplastic (MPs) change the biofilm formation rate and composition of the biofilm in comparison with the pristine MPs. To answer this question, the biofilm formation was quantified using different methods over time for both pristine polypropylene and aged polypropylene using agar plate counts and crystal violet staining. Colony counts based on agar plating showed an increase in microbial growth over the 8 weeks of treatment, with the aged MPs accumulating higher microbial counts than the pristine MPs. The diversity of the biofilm decreased over time for both MPs and the aged MPs had overall less diversity in biofilm, based on phenotype enumeration, in comparison with the pristine MPs. Higher biofilm growth on aged MPs was confirmed using crystal violet staining, which stains the negatively charged biological compounds such as proteins and the extracellular polymeric substance matrix of the biofilm. Using this complementary approach to colony counting, the same trend of higher biofilm growth on aged MPs was found. Further studies will focus on confirming the phenotype findings using microbiome analysis following DNA extraction. This project created a methodology to quantify biofilm formation on MPs, which was used to show that MPs may accumulate more biofilms in the environment as they age under sunlight.
ContributorsMushro, Noelle (Author) / Perreault, Francois (Thesis advisor) / Hamilton, Kerry (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2022
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Description
A successful implementation of a Pavement Management System (PMS) allows agencies to make objective and informed decisions in maintaining their pavement assets effectively. Since 2008, the City of Phoenix, Arizona, has implemented PMS to maintain approximately 7,725 km (4,800 mi) of pavements. PMS is not a static system but a

A successful implementation of a Pavement Management System (PMS) allows agencies to make objective and informed decisions in maintaining their pavement assets effectively. Since 2008, the City of Phoenix, Arizona, has implemented PMS to maintain approximately 7,725 km (4,800 mi) of pavements. PMS is not a static system but a dynamic system requiring regular updates to reflect pavement performance and meet the agency's goals and budget. After upgrading to the Automated Road Analyzer (ARAN) 9000 in 2017, there is a need for Phoenix to evaluate its PMS. A low pavement condition index (PCI) for newly paved roads and the requirements for more than 35% of scheduled fog seal projects to be upgraded to heavier treatments observed, also motivated this research effort. The scope of this research was limited to the flexible pavement preservation program and the objectives are: (1) to evaluate the effectiveness of the existing City of Phoenix PMS and (2) to recommend improvements to the existing PMS. This study evaluated technical and non-technical aspects of Phoenix’s preservation program. Since pavements in a structurally sound condition are good candidates for preservation treatment, a single pavement performance indicator, which allows agencies to be more flexible with their preservation treatments and minimize the pavement performance data collection and modeling efforts, was explored. A simple yet measurable and trackable pavement performance indicator, Surface Cracking Index (SCI), representing the overall pavement condition to perform PMS analysis for a preservation program, was proposed. In addition, using a performance indicator, the International Roughness Index (IRI) to represent the ride quality or roughness, is a challenge for many local governments due to the nature of urban roadway related conditions such as stop and go driving conditions, abrupt lane change maneuvering, and lower prevailing speed. Therefore, a surface roughness indicator, Mean Profile Depth (MPD) measuring pavement surface macrotexture, was explored, and is proposed to be integrated in the PMS to optimize preservation treatments and recommendation strategies. While Phoenix will directly benefit from this research study outcomes, any agency who uses PMS, or plans to use PMS for their preservation program, will also benefit from this research effort.
ContributorsN-Sang, Seng Hkawn (Author) / Kaloush, Kamil (Thesis advisor) / Medina, Jose (Committee member) / Mamlouk, Michael (Committee member) / Ozer, Hasan (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Electron Paramagnetic Resonance (EPR) has facilitated great scientific advancements in many fields, like material science, engineering, medicine, biology, and health. EPR provided the ability to investigate samples on molecular level to detect chemical composition and identify harmful substances like free radicals. This thesis aims to explore current health and diagnostics

Electron Paramagnetic Resonance (EPR) has facilitated great scientific advancements in many fields, like material science, engineering, medicine, biology, and health. EPR provided the ability to investigate samples on molecular level to detect chemical composition and identify harmful substances like free radicals. This thesis aims to explore current health and diagnostics EPR research and investigate the free radical content in related paramagnetic centers. Examining paramagnetic diagnostic markers of Cancer, Sicklecell disease, oxidative stress, and food oxidation. After exploring current literature on EPR, an experiment is designed and conducted to test seven different coffee samples (Turkish coffee, Espresso Coffee, European Coffee, Ground Arabic Coffee, American Coffee, Roasted Arabic Coffee, and Green Arabic Coffee), using Bruker ELEXSYS E580 spectrometer at x-band and under both room temperature (298 K) and low temperature (106 -113 K). Several microwave powers (1, mW, 0.25 mW, 0.16 mW, 0.06 mW, 0.04 mW) and different modulation frequency (10 G, 5 G, 3 G) are used. The results revealed average g-value was 2.009, highest linewidth was 16.312. Espresso coffee had the highest concentration of radicals, and green Arabic coffee beans had the lowest. Obtained spectra showed signals of Reactive Oxygen Species (ROS) radicals; believed to be result of natural oxidation process, as well as trace amounts of Fe3+ and other transition metals impurities, likely to be naturally found in coffee or resulting from the process of coffee production.
ContributorsMaki, Husain (Author) / Newman, Nathan (Thesis advisor) / Alford, Terry (Committee member) / Chamberlin, Ralph (Committee member) / Arizona State University (Publisher)
Created2022
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Description
The high uncertainty of renewables introduces more dynamics to power systems. The conventional way of monitoring and controlling power systems is no longer reliable. New strategies are needed to ensure the stability and reliability of power systems. This work aims to assess the use of machine learning methods in analyzing

The high uncertainty of renewables introduces more dynamics to power systems. The conventional way of monitoring and controlling power systems is no longer reliable. New strategies are needed to ensure the stability and reliability of power systems. This work aims to assess the use of machine learning methods in analyzing data from renewable integrated power systems to aid the decisionmaking of electricity market participants. Specifically, the work studies the cases of electricity price forecast, solar panel detection, and how to constrain the machine learning methods to obey domain knowledge.Chapter 2 proposes to diversify the data source to ensure a more accurate electricity price forecast. Specifically, the proposed two-stage method, namely the rerouted method, learns two types of mapping rules: the mapping between the historical wind power and the historical price and the forecasting rule for wind generation. Based on the two rules, we forecast the price via the forecasted generation and the learned mapping between power and price. The massive numerical comparison gives guidance for choosing proper machine learning methods and proves the effectiveness of the proposed method. Chapter 3 proposes to integrate advanced data compression techniques into machine learning algorithms to either improve the predicting accuracy or accelerate the computation speed. New semi-supervised learning and one-class classification methods are proposed based on autoencoders to compress the data while refining the nonlinear data representation of human behavior and solar behavior. The numerical results show robust detection accuracy, laying down the foundation for managing distributed energy resources in distribution grids. Guidance is also provided to determine the proper machine learning methods for the solar detection problem. Chapter 4 proposes to integrate different types of domain knowledge-based constraints into basic neural networks to guide the model selection and enhance interpretability. A hybrid model is proposed to penalize derivatives and alter the structure to improve the performance of a neural network. We verify the performance improvement of introducing prior knowledge-based constraints on both synthetic and real data sets.
ContributorsLuo, Shuman (Author) / Weng, Yang (Thesis advisor) / Lei, Qin (Committee member) / Fricks, John (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2022
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Description
This research paper investigates the relationship between orchestration and harmony in Prokofiev’s orchestral works through selected case studies drawn from his symphonies and several of his symphonic suites. The research focuses on moments where the combination of orchestration and harmony stand out from the orchestral texture. Prokofiev uses these two

This research paper investigates the relationship between orchestration and harmony in Prokofiev’s orchestral works through selected case studies drawn from his symphonies and several of his symphonic suites. The research focuses on moments where the combination of orchestration and harmony stand out from the orchestral texture. Prokofiev uses these two elements of music to create both a large range of orchestral colors as well as to highlight structurally important moments in thematic development. Through the selected music examples, I highlight how the two elements are mutually dependent, even synergistic. I also argue that Prokofiev uses the two elements in a highly inventive manner to create unique timbral/harmonic effects. Drawing on recent theories related to timbre and perception, the chosen segments of music are analyzed in detail within the context of the works’ form and narrative. The study of these combinations suggests further research and interpretative possibilities for composers, music theorists, and performers.
ContributorsTay, Yun Song (Author) / Meyer, Jeffery (Thesis advisor) / Schmelz, Peter (Committee member) / Bolanos, Gabriel (Committee member) / Arizona State University (Publisher)
Created2022
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Description
When most people think of Phoenix, Arizona, they think of sprawling cityscapesand hot desert mountains full of saguaros and other cacti. They rarely think of water and fish, and yet, the Arizona landscape is home to many lakes, ponds, rivers and streams, full of both native fish and sportfish, including in the

When most people think of Phoenix, Arizona, they think of sprawling cityscapesand hot desert mountains full of saguaros and other cacti. They rarely think of water and fish, and yet, the Arizona landscape is home to many lakes, ponds, rivers and streams, full of both native fish and sportfish, including in the urban areas. According to the report by DeSemple in 2006, between the years 2001 and 2006, the Rio Salado Environmental Restoration Project worked to revitalize the dry river bed that runs through Phoenix, that included the construction of two urban ponds, the Demonstration Pond and the Reservoir Pond. At the start of this study, it was unknown what vertebrate species inhabited these ponds, but it was known that these urban ponds have been used to dump unwanted aquatic pets. The bluegill Lepomis macrochirus was found to reside in both ponds, and as it is such an important sportfish species, it was chosen as the focal species for these studies, which took place over periods in March, May, July, and September of 2021. Single-season occupancy models were used to attempt to determine how L. macrochirus, use the microhabitats within the system, and a multi-season model was used to estimate their recruitment, and seasonal changes in occupancy. In addition, this study also attempts to understand the size structures of the L. macrochirus population in the Reservoir Pond and the population in the Demonstration Pond, and if that size structure varies from March to September. As the populations of these ponds are physically isolated from one another, statistical tests were also done to determine if the size structures of the two populations of L. macrochirus differ from one another and found that the two populations do indeed differ from one another, but only during two of the sampling periods.
ContributorsKeister, Emily Jan (Author) / Saul, Steven (Thesis advisor) / Bateman, Heather (Committee member) / Suzart de Albuquerque, Fabio (Committee member) / Arizona State University (Publisher)
Created2022
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Description
In a Mirror Dimly… is an autobiographical work that follows my mental development from my teen years into my mid-20s and offers a way forward into the future. First comes legalism: a canon, which represents a rule-based thought process. Next is freedom and individuality: indeterminate methods and textures. Finally, the

In a Mirror Dimly… is an autobiographical work that follows my mental development from my teen years into my mid-20s and offers a way forward into the future. First comes legalism: a canon, which represents a rule-based thought process. Next is freedom and individuality: indeterminate methods and textures. Finally, the piece concludes with unity and wholeness, using quoted and composed hymns in chorale settings. The conceptual content is taken from Hermann Hesse’s Siddhartha, a story of a Hindu man’s life through the development of his own ideology into Buddhism. He begins by following the rules of his faith obsessively, then he decides that the rules themselves don’t matter as much as the spirit behind them, and finally he begins to see the interconnectedness of nature through the flow of a river and gains a fuller picture of all that is. I have also included an anxiety motif which begins as an interruption or nuisance; it then takes over in the form of a panic attack but is quelled by a hymn: “Be Still My Soul,” with text written by Katharina von Schlegel set to the tune of Sibelius’ Finlandia. Finally, the anxiety is contained and molded to help the overall texture rather than disrupting it. The anxiety is never truly eradicated, but it is transformed.
ContributorsChesney, Jacob Andrew (Author) / Temple, Alex (Thesis advisor) / Bolanos, Gabriel (Committee member) / Rockmaker, Jody (Committee member) / Arizona State University (Publisher)
Created2022