Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

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Description
Object localization is used to determine the location of a device, an important aspect of applications ranging from autonomous driving to augmented reality. Commonly-used localization techniques include global positioning systems (GPS), simultaneous localization and mapping (SLAM), and positional tracking, but all of these methodologies have drawbacks, especially in high traffic

Object localization is used to determine the location of a device, an important aspect of applications ranging from autonomous driving to augmented reality. Commonly-used localization techniques include global positioning systems (GPS), simultaneous localization and mapping (SLAM), and positional tracking, but all of these methodologies have drawbacks, especially in high traffic indoor or urban environments. Using recent improvements in the field of machine learning, this project proposes a new method of localization using networks with several wireless transceivers and implemented without heavy computational loads or high costs. This project aims to build a proof-of-concept prototype and demonstrate that the proposed technique is feasible and accurate.

Modern communication networks heavily depend upon an estimate of the communication channel, which represents the distortions that a transmitted signal takes as it moves towards a receiver. A channel can become quite complicated due to signal reflections, delays, and other undesirable effects and, as a result, varies significantly with each different location. This localization system seeks to take advantage of this distinctness by feeding channel information into a machine learning algorithm, which will be trained to associate channels with their respective locations. A device in need of localization would then only need to calculate a channel estimate and pose it to this algorithm to obtain its location.

As an additional step, the effect of location noise is investigated in this report. Once the localization system described above demonstrates promising results, the team demonstrates that the system is robust to noise on its location labels. In doing so, the team demonstrates that this system could be implemented in a continued learning environment, in which some user agents report their estimated (noisy) location over a wireless communication network, such that the model can be implemented in an environment without extensive data collection prior to release.
ContributorsChang, Roger (Co-author) / Kann, Trevor (Co-author) / Alkhateeb, Ahmed (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper, we propose to use Topological Data Analysis (TDA) together with machine learning tools to automate the process of Parkinson’s disease classification and severity assessment.

At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper, we propose to use Topological Data Analysis (TDA) together with machine learning tools to automate the process of Parkinson’s disease classification and severity assessment. An automated, stable, and accurate method to evaluate Parkinson’s would be significant in streamlining diagnoses of patients and providing families more time for corrective measures. We propose a methodology which incorporates TDA into analyzing Parkinson’s disease postural shifts data through the representation of persistence images. Studying the topology of a system has proven to be invariant to small changes in data and has been shown to perform well in discrimination tasks. The contributions of the paper are twofold. We propose a method to 1) classify healthy patients from those afflicted by disease and 2) diagnose the severity of disease. We explore the use of the proposed method in an application involving a Parkinson’s disease dataset comprised of healthy-elderly, healthy-young and Parkinson’s disease patients.
ContributorsRahman, Farhan Nadir (Co-author) / Nawar, Afra (Co-author) / Turaga, Pavan (Thesis director) / Krishnamurthi, Narayanan (Committee member) / Electrical Engineering Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
Complex human controls is a topic of much interest in the fields of robotics, manufacturing, space exploration and many others. Even simple tasks that humans perform with ease can be extremely complicated when observed from a controls and complex systems perspective. One such simple task is that of a human

Complex human controls is a topic of much interest in the fields of robotics, manufacturing, space exploration and many others. Even simple tasks that humans perform with ease can be extremely complicated when observed from a controls and complex systems perspective. One such simple task is that of a human carrying and moving a coffee cup. Though this may be a mundane task for humans, when this task is modelled and analyzed, the system may be quite chaotic in nature. Understanding such systems is key to the development robots and autonomous systems that can perform these tasks themselves.

The coffee cup system can be simplified and modeled by a cart-and-pendulum system. Bazzi et al. and Maurice et al. present two different cart-and-pendulum systems to represent the coffee cup system [1],[2]. The purpose of this project was to build upon these systems and to gain a better understanding of the coffee cup system and to determine where chaos existed within the system. The honors thesis team first worked with their senior design group to develop a mathematical model for the cart-and-pendulum system based on the Bazzi and Maurice papers [1],[2]. This system was analyzed and then built upon by the honors thesis team to build a cart-and-two-pendulum model to represent the coffee cup system more accurately.

Analysis of the single pendulum model showed that there exists a low frequency region where the pendulum and the cart remain in phase with each other and a high frequency region where the cart and pendulum have a π phase difference between them. The transition point of the low and high frequency region is determined by the resonant frequency of the pendulum. The analysis of the two-pendulum system also confirmed this result and revealed that differences in length between the pendulum cause the pendulums to transition to the high frequency regions at separate frequency. The pendulums have different resonance frequencies and transition into the high frequency region based on their own resonant frequency. This causes a range of frequencies where the pendulums are out of phase from each other. After both pendulums have transitioned, they remain in phase with each other and out of phase from the cart.

However, if the length of the pendulum is decreased too much, the system starts to exhibit chaotic behavior. The short pendulum starts to act in a chaotic manner and the phase relationship between the pendulums and the carts is no longer maintained. Since the pendulum length represents the distance between the particle of coffee and the top of the cup, this implies that coffee near the top of the cup would cause the system to act chaotically. Further analysis would be needed to determine the reason why the length affects the system in this way.
ContributorsZindani, Abdul Rahman (Co-author) / Crane, Kari (Co-author) / Lai, Ying-Cheng (Thesis director) / Jiang, Junjie (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
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Description
Machine learning is a powerful tool for processing and understanding the vast amounts of data produced by sensors every day. Machine learning has found use in a wide variety of fields, from making medical predictions through correlations invisible to the human eye to classifying images in computer vision applications. A

Machine learning is a powerful tool for processing and understanding the vast amounts of data produced by sensors every day. Machine learning has found use in a wide variety of fields, from making medical predictions through correlations invisible to the human eye to classifying images in computer vision applications. A wide range of machine learning algorithms have been developed to attempt to solve these problems, each with different metrics in accuracy, throughput, and energy efficiency. However, even after they are trained, these algorithms require substantial computations to make a prediction. General-purpose CPUs are not well-optimized to this task, so other hardware solutions have developed over time, including the use of a GPU, FPGA, or ASIC.

This project considers the FPGA implementations of MLP and CNN feedforward. While FPGAs provide significant performance improvements, they come at a substantial financial cost. We explore the options of implementing these algorithms on a smaller budget. We successfully implement a multilayer perceptron that identifies handwritten digits from the MNIST dataset on a student-level DE10-Lite FPGA with a test accuracy of 91.99%. We also apply our trained network to external image data loaded through a webcam and a Raspberry Pi, but we observe lower test accuracy in these images. Later, we consider the requirements necessary to implement a more elaborate convolutional neural network on the same FPGA. The study deems the CNN implementation feasible in the criteria of memory requirements and basic architecture. We suggest the CNN implementation on the same FPGA to be worthy of further exploration.
ContributorsLythgoe, Zachary James (Author) / Allee, David (Thesis director) / Hartin, Olin (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
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Description
Strong Mothers Strong Teeth is an initiative to educate mothers and pregnant women about the importance of maintaining their own and their child(ren)’s oral health. This project presents evidence that shows a lack of oral health education among mothers about how to care for their oral health while pregnant and

Strong Mothers Strong Teeth is an initiative to educate mothers and pregnant women about the importance of maintaining their own and their child(ren)’s oral health. This project presents evidence that shows a lack of oral health education among mothers about how to care for their oral health while pregnant and their child’s oral health post birth. The recognition and identification of these disparities led to the content deemed necessary to be included in the education of mothers and pregnant women. By collecting and analyzing pamphlets and information gathered from health clinics and homeless shelters in Arizona and California, we created our own pamphlets based on analysis of the effectiveness of the information using content analysis and Flesch-Kincaid readability scores. This led to the creation of two pamphlets to educate mothers on oral health care, the first focused on preventing tooth decay in women during their pregnancy and for their baby, post-birth, and the second provided a timeline guide on oral health for the mother and child.
ContributorsBlair, Grace (Co-author) / Patel, Toral (Co-author) / Loebenberg, Abby (Thesis director) / Magee, Mitch (Committee member) / School of Social Transformation (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
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Description
With the revolution of low-cost microelectronics, rotary-wing vehicles have grown increasingly popular and important in the past two decades. With increased interest in quadcopters comes the need to for a systematic and rigorous framework to model, analyze, control, and design them. This thesis presents the beginning of such a framework.

With the revolution of low-cost microelectronics, rotary-wing vehicles have grown increasingly popular and important in the past two decades. With increased interest in quadcopters comes the need to for a systematic and rigorous framework to model, analyze, control, and design them. This thesis presents the beginning of such a framework.

The work presents the nonlinear equations of motion of a quadcopter. This includes the translational and rotational equations of motion, as well as an analysis of the nonlinear actuator dynamics. The work then analyzes the static properties of a quadcopter in forward flight equilibrium and shows how static properties change as physical properties of the vehicle are varied. Next, the dynamics of forward flight are linearized, and a dynamic analysis is provided.

After dynamic analysis, the work shows detailed hierarchical control system design trade studies, which includes attitude and translational inner-outer loop control. Among other designs, the following are presented: PD control, proportional control, pole-placement control. Each of these control architectures are employed for the inner loops and outer loops. The work also analyzes linear versus nonlinear simulation performance of a quadcopter, specifically for a step x-axis reference command. It is found that the nonlinear dynamics of the actuator cause significant discrepancy between linear and nonlinear simulation.

Finally, this thesis establishes directions for future graduate research. This includes hardware design, as well as moving toward design of a highly-maneuverable thrust-vectoring quadrotor which will be the focus of the proposed graduate PhD research. In summary, this thesis provides the beginning of a cohesive framework to model, analyze, control, and design quadcopters. It also lays the groundwork for graduate research and beyond.
ContributorsWallace, Brent (Author) / Rodriguez, Armando (Thesis director) / Berman, Spring (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
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Description
This paper will primarily deal with obstacle detection and the benefits that radar technology provides as the primary interface. The concept that is being proposed involves using a non-industrialized radar to achieve similar results when trying to detect a present object. By being able to achieve a working radar detection

This paper will primarily deal with obstacle detection and the benefits that radar technology provides as the primary interface. The concept that is being proposed involves using a non-industrialized radar to achieve similar results when trying to detect a present object. By being able to achieve a working radar detection system at a more general domain, the path to it becoming more universal accessible increases. This, in turn, will hopefully amplify the areas in which radar technology can be applied to and lead to great benefits universally. From the compiled data and the work that has been done to achieve a responsive radar, it is noted that the radar will provide an accurate reading in most conditions that it is introduced to. These conditions vary from range resolution aspects to various weather environments, as well as the visibility aspect. However, based on the results that were achieved, through various testing, there are still some areas in which radar technology needs to improve in, for it to be fully considered as the sole interface when it comes to obstacle detection and its integration into future technology like self-driving cars. Nevertheless, the capabilities of radar technology at this caliber is noted to be quite impressive and similar to other more expansive options that are available.
ContributorsMartinez, Johan (Author) / Yu, Hongbin (Thesis director) / Houghton, Todd (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
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Description
In the field of electronic music, haptic feedback is a crucial feature of digital musical instruments (DMIs) because it gives the musician a more immersive experience. This feedback might come in the form of a wearable haptic device that vibrates in response to music. Such advancements in the electronic music

In the field of electronic music, haptic feedback is a crucial feature of digital musical instruments (DMIs) because it gives the musician a more immersive experience. This feedback might come in the form of a wearable haptic device that vibrates in response to music. Such advancements in the electronic music field are applicable to the field of speech and hearing. More specifically, wearable haptic feedback devices can enhance the musical listening experience for people who use cochlear implant (CI) devices.
This Honors Thesis is a continuation of Prof. Lauren Hayes’s and Dr. Xin Luo’s research initiative, Haptic Electronic Audio Research into Musical Experience (HEAR-ME), which investigates how to enhance the musical listening experience for CI users using a wearable haptic system. The goals of this Honors Thesis are to adapt Prof. Hayes’s system code from the Max visual programming language into the C++ object-oriented programming language and to study the results of the developed C++ codes. This adaptation allows the system to operate in real-time and independently of a computer.
Towards these goals, two signal processing algorithms were developed and programmed in C++. The first algorithm is a thresholding method, which outputs a pulse of a predefined width when the input signal falls below some threshold in amplitude. The second algorithm is a root-mean-square (RMS) method, which outputs a pulse-width modulation signal with a fixed period and with a duty cycle dependent on the RMS of the input signal. The thresholding method was found to work best with speech, and the RMS method was found to work best with music. Future work entails the design of adaptive signal processing algorithms to allow the system to work more effectively on speech in a noisy environment and to emphasize a variety of elements in music.
ContributorsBonelli, Dominic Berlage (Author) / Papandreou-Suppappola, Antonia (Thesis director) / Hayes, Lauren (Thesis director, Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
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Description
The Java-Bali power system is the biggest power system in Indonesia. On September 5th, 2018 at 11:26 AM, a region in the East Java-Bali subsystem suffered a blackout due to a single line to ground fault that disrupted the stability of the interconnected system and caused cascaded tripping.

This thesis

The Java-Bali power system is the biggest power system in Indonesia. On September 5th, 2018 at 11:26 AM, a region in the East Java-Bali subsystem suffered a blackout due to a single line to ground fault that disrupted the stability of the interconnected system and caused cascaded tripping.

This thesis presents the results of an evaluation of the dynamic performance of the East Java-Bali subsystem. It involves the static and dynamic simulations of the sequence of events that led to the East Java Bali subsystem blackout, especially the impact of the loss of a set of 500 kV transmission lines, which in reality was suspected to be the main cause.

The basic calculations related to power system state and familiarization with PSS/E (a commercial power system analysis software package) are first demonstrated. A simple 3-bus system test is taken as an example. The steady state characteristics of the active and reactive power injection, voltage and phase angle are calculated manually and compared to the PSS/E simulation results. As for the dynamic characteristics, short circuit current, electrical and mechanical power, rotor angle, and fault clearing time are determined by observing the plots of the simulation results. Based on understanding of the PSS/E modeling and simulation, the configuration, generation, and loading of the simplified East Java-Bali subsystem is evaluated. The generators (including the excitation system and governor) and transmission lines parameters are updated, as the reference model for the study. The model is validated by the actual data (active power flow) before the fault. Single line to ground fault and loss of generation disturbances were simulated to observe the stability of the system.

The analysis of the blackout is conducted through the simulation results based on all relevant documentation (such as fault report and sequence of events). With respect to the sequence of events (a single line to ground fault on the 500kV transmission lines, overload on 150kV transmission lines and tripping of power plants), several simulations of the East Java-Bali subsystem operations provided in the official blackout report are evaluated. Finally, the undervoltage load shedding strategy is evaluated and proposed as a solution to mitigate the blackout in the East Java-Bali subsystem.

The simulations reveal some interesting results regarding the operational characteristics of the East Java-Bali subsystem before the disturbances and during the cascaded tripping.
ContributorsRoekman, Taufan Marviansha (Author) / Vittal, Vijay (Thesis director) / Pal, Anamitra (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
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Description
The purpose of this thesis project is to analyze the impact that patient death has on long-term care providers. This study draws upon my own experience working as a licensed nursing assistant in a long-term care facility and also uses a qualitative analysis of six semi-structured interviews with other nursing

The purpose of this thesis project is to analyze the impact that patient death has on long-term care providers. This study draws upon my own experience working as a licensed nursing assistant in a long-term care facility and also uses a qualitative analysis of six semi-structured interviews with other nursing assistants and hospice volunteers. With patient death being an unavoidable part of working in this area of healthcare, I explore how these care providers cope with losing their patients and the effectiveness of these coping mechanisms. Some strategies found that aided in coping with grief included staying detached from patients, being distracted by other aspects of the job, receiving support from co-workers, family members and/or supervisors, and having a religious outlook on what happens following death. In addition to these, I argue that care providers also utilize the unconscious defense mechanism of repression to avoid their feelings of grief and guilt. Repressing the grief and emotions that come along with patient death can protect the individual from additional pain in order for them to continue to do their difficult jobs. Being distracted by other patients also aids in the repression process by avoiding personal feelings temporarily. I also look into factors that have been found to affect the level of grief including the caregiver’s closeness to the patient, level of preparedness for the death, and first experience of losing a patient. Ultimately, I show that the common feelings accompanied by patient death (sadness, anger and stress) and the occurrence of burnout are harmful symptoms of the repression taking place.
ContributorsMasterson, Kaitlin (Author) / Loebenberg, Abby (Thesis director) / Mack, Robert (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05