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This thesis dives into the world of artificial intelligence by exploring the functionality of a single layer artificial neural network through a simple housing price classification example while simultaneously considering its impact from a data management perspective on both the software and hardware level. To begin this study, the universally

This thesis dives into the world of artificial intelligence by exploring the functionality of a single layer artificial neural network through a simple housing price classification example while simultaneously considering its impact from a data management perspective on both the software and hardware level. To begin this study, the universally accepted model of an artificial neuron is broken down into its key components and then analyzed for functionality by relating back to its biological counterpart. The role of a neuron is then described in the context of a neural network, with equal emphasis placed on how it individually undergoes training and then for an entire network. Using the technique of supervised learning, the neural network is trained with three main factors for housing price classification, including its total number of rooms, bathrooms, and square footage. Once trained with most of the generated data set, it is tested for accuracy by introducing the remainder of the data-set and observing how closely its computed output for each set of inputs compares to the target value. From a programming perspective, the artificial neuron is implemented in C so that it would be more closely tied to the operating system and therefore make the collected profiler data more precise during the program's execution. The program is designed to break down each stage of the neuron's training process into distinct functions. In addition to utilizing more functional code, the struct data type is used as the underlying data structure for this project to not only represent the neuron but for implementing the neuron's training and test data. Once fully trained, the neuron's test results are then graphed to visually depict how well the neuron learned from its sample training set. Finally, the profiler data is analyzed to describe how the program operated from a data management perspective on the software and hardware level.
ContributorsRichards, Nicholas Giovanni (Author) / Miller, Phillip (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Even in the largest public university in the country, computer related degrees such as Computer Science, Computer Systems Engineering and Software Engineering have low enrollment rates and high dropout rates. This is interesting because the careers that require these degrees are marketed as the highest paying and most powerful. The

Even in the largest public university in the country, computer related degrees such as Computer Science, Computer Systems Engineering and Software Engineering have low enrollment rates and high dropout rates. This is interesting because the careers that require these degrees are marketed as the highest paying and most powerful. The goal of this project was to find out what the students of Arizona State University (ASU) thought about these majors and why they did or did not pick them. A total of 206 students were surveyed from a variety of sources including upper level classes, lower level classes and Barrett, the Honors College. Survey questions asked why the students picked their current major, if they had a previous major and why did they switch, and if the students had considered one of the three computer related degrees. Almost all questions were open ended, meaning the students did not have multiple choice answers and instead could write as short or as long of a response as needed. Responses were grouped based on a set of initial hypotheses and any emerging trends. These groups were displayed in several different bar graphs broken down by gender, grade level and category of student (stayed in a computer related degree, left one, joined one or picked a non-computer related degree). Trends included students of all grade levels picking their major because they were passionate or interested in the subject. This may suggest that college students are set in their path and will not switch majors easily. Students also reported seeing computer related degrees as too difficult and intimidating. However, given the low (when compared to all of ASU) number of students surveyed, the conclusions and trends given cannot be representative of ASU as a whole. Rather, they are just representative of this sample population. Further work on this study, if time permitted, would be to try to survey more students and question some of the trends established to find more specific answers.
ContributorsMeza, Edward L (Author) / Meuth, Ryan (Thesis director) / Miller, Phillip (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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Description

A project about developing software for learning turned into a project for learning about software development. The submission here only includes the journal. However, the journal has a link to the public GitHub repository containing the source code for the thesis. The source code implements a program to facilitate self-study

A project about developing software for learning turned into a project for learning about software development. The submission here only includes the journal. However, the journal has a link to the public GitHub repository containing the source code for the thesis. The source code implements a program to facilitate self-study by allowing the user to create quizzes. The journal contains my experience working on the project (both successes and failures).

ContributorsRoper, Branden Gerald (Author) / Miller, Phillip (Thesis director) / Zazkis, Dov (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Arizona State course enrollment regularly reaches triple digits. Despite the large enrollment numbers, the level of communication among students remain relatively low. Students often create Discord servers to keep in touch with classmates, but this requires each individual student to track down the invite link. The purpose of this project

Arizona State course enrollment regularly reaches triple digits. Despite the large enrollment numbers, the level of communication among students remain relatively low. Students often create Discord servers to keep in touch with classmates, but this requires each individual student to track down the invite link. The purpose of this project is to create an inviting chat service for students with minimal barriers of entry. This website, https://gibbl.io, offers a chat room for every class at ASU, making it simple for students to maintain communication.

Created2021-05
Description

This creative project develops an environment in which three species inhabit a shared land and models the movement of the creatures to determine the survival rates over time in specific conditions. The three species modelled include a predator and a prey species with movement capabilities as well as a stagnant

This creative project develops an environment in which three species inhabit a shared land and models the movement of the creatures to determine the survival rates over time in specific conditions. The three species modelled include a predator and a prey species with movement capabilities as well as a stagnant fruit species. There are a variety of configurable variables that can be used to modify and control the simulation to observe how the resulting population charts change. The big difference between this project and a normal approach to simulating a predation relationship is that actual creatures themselves are being created and their movement is simulated in this virtual environment which then leads to population counts, rather than integrating differential equations relating the population sizes of both species and purely tracking the populations but not the creatures themselves. Because of this difference, my simulation is not meant to handle all the complexities of life that come in the real-world but instead is intended as a simplified approach to simulating creatures' lives with the purpose of conveying the idea of a real predation relationship. Thus, the main objective of my simulation is to produce data representative of real-world predator-prey relationships, with the overall cyclical pattern that is observed in natural achieved through simulating creature movement and life itself rather than estimating population size change.

ContributorsPerry, Jordan (Author) / Burger, Kevin (Thesis director) / Miller, Phillip (Committee member) / Barrett, The Honors College (Contributor) / Department of Physics (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description
This project seeks to motivate runners by creating an application that selectively plays music based on smartwatch metrics. This is done by analyzing metrics collected through a person’s smartwatch such as heart rate or running power and then selecting the music that best fits their workout’s intensity. This way, as

This project seeks to motivate runners by creating an application that selectively plays music based on smartwatch metrics. This is done by analyzing metrics collected through a person’s smartwatch such as heart rate or running power and then selecting the music that best fits their workout’s intensity. This way, as the workout becomes harder for the user, increasingly motivating music is played.
ContributorsDoyle, Niklas (Author) / Osburn, Steven (Thesis director) / Miller, Phillip (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Music, Dance and Theatre (Contributor)
Created2023-05
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Description
The most important task for a beginning computer science student, in order for them to succeed in their future studies, is to learn to be able to understand code. One of the greatest indicators of student success in beginning programming courses is the ability to read code and predict its

The most important task for a beginning computer science student, in order for them to succeed in their future studies, is to learn to be able to understand code. One of the greatest indicators of student success in beginning programming courses is the ability to read code and predict its output, as this shows that the student truly understands what each line of code is doing. Yet few tools available to students today focus on helping students to improve their ability to read code. The goal of the random Python program generator is to give students a tool to practice this important skill.

The program writes randomly generated, syntactically correct Python 3 code in order to provide students infinite examples from which to study. The end goal of the project is to create an interactive tool where beginning programming students can click a button to generate a random code snippet, check if what they predict the output to be is correct, and get an explanation of the code line by line. The tool currently lacks a front end, but it currently is able to write Python code that includes assignment statements, delete statements, if statements, and print statements. It supports boolean, float, integer, and string variable types.
ContributorsDiLorenzo, Kaitlyn (Author) / Meuth, Ryan (Thesis director) / Miller, Phillip (Committee member) / School of International Letters and Cultures (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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ContributorsVadlamudi, Srisushanth (Author) / Solis, Jalen (Co-author) / Miller, Phillip (Thesis director) / De Luca, Gennaro (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Natural Sciences (Contributor)
Created2022-05
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ContributorsVadlamudi, Srisushanth (Author) / Solis, Jalen (Co-author) / Miller, Phillip (Thesis director) / De Luca, Gennaro (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Natural Sciences (Contributor)
Created2022-05
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ContributorsSolis, Jalen (Author) / Vadlamudi, Sai (Co-author) / Miller, Phillip (Thesis director) / De Luca, Gennaro (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05