Matching Items (61)
Description

Nowadays, kids are exposed to technology at an incredibly early age. According to a study by YouGov in the United Kingdom, 88% of 12-year-olds are entrusted with their own devices and 85% of children at age 6 have access to a tablet at home (YouGov). In the US, according to

Nowadays, kids are exposed to technology at an incredibly early age. According to a study by YouGov in the United Kingdom, 88% of 12-year-olds are entrusted with their own devices and 85% of children at age 6 have access to a tablet at home (YouGov). In the US, according to MarketingProfs 75% of children 8 and under have access to some type of smart device. In an ever-growing technological world, it is important to make sure that kids are enjoying entertainment that enhances their growth and protects them from inappropriate content (Nanji). I wanted to create a browser game that explains the importance of Security in a colorful, fun environment with a friendly playable character. The game I created is a 2D platformer in which the player learns about the importance of passwords and keeping them secure.

ContributorsMichalik, Jacob (Author) / Meuth, Ryan (Thesis director) / Kobayashi, Yoshihiro (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description

Personal electric vehicles, or PEVs, help individuals navigate short to mid distance commutes in environments that lack effective public transportation solutions. This is known as the “Last Mile” problem. A particular solution, electric skateboards, are highly energy efficient due to their size but lack auxiliary features for safety and user-convenience

Personal electric vehicles, or PEVs, help individuals navigate short to mid distance commutes in environments that lack effective public transportation solutions. This is known as the “Last Mile” problem. A particular solution, electric skateboards, are highly energy efficient due to their size but lack auxiliary features for safety and user-convenience connected to the same battery supply. Plus, almost all conventional electric boards come with proprietary software and hardware designs, meaning that modifying or improving upon their logic is extremely difficult if not impossible. Therefore, our group aims to prototype an improved, open-source electric skateboard design to determine the feasibility of our ideas.

ContributorsGarcia, Brendan (Author) / Woodburne, Ian (Co-author) / Meuth, Ryan (Thesis director) / Michael, Katina (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description

Personal electric vehicles, or PEVs, help individuals navigate short to mid distance commutes in environments that lack effective public transportation solutions. This is known as the “Last Mile” problem. A particular solution, electric skateboards, are highly energy efficient due to their size but lack auxiliary features for safety and user-convenience

Personal electric vehicles, or PEVs, help individuals navigate short to mid distance commutes in environments that lack effective public transportation solutions. This is known as the “Last Mile” problem. A particular solution, electric skateboards, are highly energy efficient due to their size but lack auxiliary features for safety and user-convenience connected to the same battery supply. Plus, almost all conventional electric boards come with proprietary software and hardware designs, meaning that modifying or improving upon their logic is extremely difficult if not impossible. Therefore, our group aims to prototype an improved, open-source electric skateboard design to determine the feasibility of our ideas.

ContributorsWoodburne, Ian (Author) / Garcia, Brendan (Co-author) / Meuth, Ryan (Thesis director) / Michael, Katina (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
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Description
Now that home security systems are readily available at a low cost, these systems are commonly being installed to watch over homes and loved ones. These systems are fairly easy to install and can provide 4k Ultra HD resolution. The user can configure the sensitivity and areas to monitor and

Now that home security systems are readily available at a low cost, these systems are commonly being installed to watch over homes and loved ones. These systems are fairly easy to install and can provide 4k Ultra HD resolution. The user can configure the sensitivity and areas to monitor and receive object detection notifications. Unfortunately, once the customer starts to use the system, they often find that the notifications are overwhelming and soon turn them off. After hearing the same experience from multiple friends and family I thought it would be a good topic for my thesis. I examined a top selling security system sold at a bulk retail store and have implemented improved detection techniques that advance object detection and reduce false notifications. The additional algorithms will support the processing of both near real-time streams and saved video file processing, which existing security systems do not include.
ContributorsBustillos, Adriana (Author) / Meuth, Ryan (Thesis director) / Nakamura, Mutsumi (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
Description

Among classes in the Computer Science curriculum at Arizona State University, Automata Theory is widely considered to be one of the most difficult. Many Computer Science concepts have strong visual components that make them easier to understand. Binary trees, Dijkstra's algorithm, pointers, and even more basic concepts such as arrays

Among classes in the Computer Science curriculum at Arizona State University, Automata Theory is widely considered to be one of the most difficult. Many Computer Science concepts have strong visual components that make them easier to understand. Binary trees, Dijkstra's algorithm, pointers, and even more basic concepts such as arrays all have very strong visual components. Not only that, but resources for them are abundantly available online. Automata Theory, on the other hand, is the first Computer Science course students encounter that has a significant focus on deep theory. Many of the concepts can be difficult to visualize, or at least take a lot of effort to do so. Furthermore, visualizers for finite state machines are hard to come by. Because I thoroughly enjoyed learning about Automata Theory and parsers, I wanted to create a program that involved the two. Additionally, I thought creating a program for visualizing automata would help students who struggle with Automata Theory develop a stronger understanding of it.

ContributorsSmith, Andrew (Author) / Burger, Kevin (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor)
Created2021-12
Description

This project tackles a real-world example of a classroom with college students to discover what factors affect a student’s outcome in the class as well as investigate when and why a student who started well in the semester may end poorly later on. First, this project performs a statistical analysis

This project tackles a real-world example of a classroom with college students to discover what factors affect a student’s outcome in the class as well as investigate when and why a student who started well in the semester may end poorly later on. First, this project performs a statistical analysis to ensure that the total score of a student is truly based on the factors given in the dataset instead of due to random chance. Next, factors that are the most significant in affecting the outcome of scores in zyBook assignments are discovered. Thirdly, visualization of how students perform over time is displayed for the student body as a whole and students who started well at the beginning of the semester but trailed off towards the end. Lastly, the project also gives insight into the failure metrics for good starter students who unfortunately did not perform as well later in the course.

ContributorsChung, Michael (Author) / Meuth, Ryan (Thesis director) / Samara, Marko (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description
In response to the lasting negative effects of the COVID-19 pandemic on driver’s education and road safety, this thesis is intended to create an iOS application that recognizes and reports on poor driving habits. The end user opens the application to start a trip, the application records GPS data and

In response to the lasting negative effects of the COVID-19 pandemic on driver’s education and road safety, this thesis is intended to create an iOS application that recognizes and reports on poor driving habits. The end user opens the application to start a trip, the application records GPS data and information from APIs containing environmental information in a consistent, synchronized manner, patterns in said data are analyzed by the application to flag events representing different issues when driving, and when the user presses a button to end the trip, a report of the events is presented. The project was developed using a complete design process, including a full Research and Development process and detailed design documentation. Separate components of the application were developed in an iterative structure, with GPS information, the data synchronization system, API parsing and recording, data analysis, and feedback all being designed and tested separately. The application ultimately reached late beta status, with target stability and test results being achieved in typical use cases.
ContributorsBronzi, John (Author) / Meuth, Ryan (Thesis director) / Yee, Richard (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-12
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Description
5G Millimeter Wave (mmWave) technology holds great promise for Connected Autonomous Vehicles (CAVs) due to its ability to achieve data rates in the Gbps range. However, mmWave suffers high beamforming overhead and requirement of line of sight (LOS) to maintain a strong connection. For Vehicle-to-Infrastructure (V2I) scenarios, where CAVs connect

5G Millimeter Wave (mmWave) technology holds great promise for Connected Autonomous Vehicles (CAVs) due to its ability to achieve data rates in the Gbps range. However, mmWave suffers high beamforming overhead and requirement of line of sight (LOS) to maintain a strong connection. For Vehicle-to-Infrastructure (V2I) scenarios, where CAVs connect to roadside units (RSUs), these drawbacks become apparent. Because vehicles are dynamic, there is a large potential for link blockages, which in turn is detrimental to the connected applications running on the vehicle, such as cooperative perception and remote driver takeover. Existing RSU selection schemes base their decisions on signal strength and vehicle trajectory alone, which is not enough to prevent the blockage of links. Most recent CAVs motion planning algorithms routinely use other vehicle's near-future plans, either by explicit communication among vehicles, or by prediction. In this thesis, I make use of this knowledge (of the other vehicle's near future path plans) to further improve the RSU association mechanism for CAVs. I solve the RSU association problem by converting it to a shortest path problem with the objective to maximize the total communication bandwidth. Evaluations of B-AWARE in simulation using Simulated Urban Mobility (SUMO) and Digital twin for self-dRiving Intelligent VEhicles (DRIVE) on 12 highway and city street scenarios with varying traffic density and RSU placements show that B-AWARE results in a 1.05x improvement of the potential datarate in the average case and 1.28x in the best case vs. the state of the art. But more impressively, B-AWARE reduces the time spent with no connection by 48% in the average case and 251% in the best case as compared to the state-of-the-art methods. This is partly a result of B-AWARE reducing almost 100% of blockage occurrences in simulation.
ContributorsSzeto, Matthew (Author) / Shrivastava, Aviral (Thesis advisor) / LiKamWa, Robert (Committee member) / Meuth, Ryan (Committee member) / Arizona State University (Publisher)
Created2023
Description
The number of extreme wildfires is on the rise globally, and predicting the size of a fire will help officials make appropriate decisions to mitigate the risk the fire poses against the environment and humans. This study attempts to find the burned area of fires in the United States based

The number of extreme wildfires is on the rise globally, and predicting the size of a fire will help officials make appropriate decisions to mitigate the risk the fire poses against the environment and humans. This study attempts to find the burned area of fires in the United States based on attributes such as time, weather, and location of the fire using machine learning methods.
ContributorsPrabagaran, Padma (Author, Co-author) / Meuth, Ryan (Thesis director) / McCulloch, Robert (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-12
Description
This study aims to combine the wisdom of crowds with ML to make more accurate stock price predictions for a select set of stocks. Different from prior works, this study uses different input elicitation techniques to improve crowd performance. In addition, machine learning is used to support the crowd. The

This study aims to combine the wisdom of crowds with ML to make more accurate stock price predictions for a select set of stocks. Different from prior works, this study uses different input elicitation techniques to improve crowd performance. In addition, machine learning is used to support the crowd. The influence of ML on the crowd is tested by priming participants with suggestions from an ML model. Lastly, the market conditions and stock popularity is observed to better understand crowd behavior.
ContributorsBhogaraju, Harika (Author) / Escobedo, Adolfo R (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-12