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- All Subjects: Computer Science
- All Subjects: robotics
- Creators: Computer Science and Engineering Program
DescriptionA two-way deterministic finite pushdown automaton ("2PDA") is developed for the Lua language. This 2PDA is evaluated against both a purpose-built Lua syntax test suite and the test suite used by the reference implementation of Lua, and fully passes both.
ContributorsStevens, Kevin A (Author) / Shoshitaishvili, Yan (Thesis director) / Wang, Ruoyu (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Learning to code is a skill that is becoming increasing needed as technology advances, yet is absent in traditional education. This thesis aims to provide a resource for middle school teachers to introduce programming skills and concepts to their students over several lessons designed to fit within the constraints of a standard class period. By targeting students in middle school, if they develop an interest, they will have enough time in middle or high school to prepare themselves for a degree in Computer Science or to complete a programming boot camp after they graduate high school. Additionally, middle school students are old enough to understand challenging programming concepts and work together to solve a programming challenge. The programming language and environment, VIPLE, will be used to teach the concepts in the lessons as it is a graphical programming language, which removes many of the common challenges faced by young students in learning to code, like dealing with syntax or remembering keywords for coding blocks.
ContributorsBelt, Emily (Author) / Chen, Yinong (Thesis director) / Miller, Cindy (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Alife is an event searching and event publishing website written in C# using the MVC software design pattern. Alife aims to offer a platform for student organizations to publish their events while enabling ASU students to browse, search, and filter events based on date, location, keywords, and category tags. Alife can also retrieve events information from the official ASU Event website, parse the keywords of the events and assign category tags to them. Alife project explores many concepts of Distributed Service-Oriented software development, such as server-side development, MVC architecture, client-side development, database integration, web service development and consuming.
ContributorsWu, Mengqi (Author) / Chen, Yinong (Thesis director) / Feng, Xuerong (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Machine learning is one of the fastest growing fields and it has applications in almost any industry. Predicting sports games is an obvious use case for machine learning, data is relatively easy to collect, generally complete data is available, and outcomes are easily measurable. Predicting the outcomes of sports events may also be easily profitable, predictions can be taken to a sportsbook and wagered on. A successful prediction model could easily turn a profit. The goal of this project was to build a model using machine learning to predict the outcomes of NBA games.
In order to train the model, data was collected from the NBA statistics website. The model was trained on games dating from the 2010 NBA season through the 2017 NBA season. Three separate models were built, predicting the winner, predicting the total points, and finally predicting the margin of victory for a team. These models learned on 80 percent of the data and validated on the other 20 percent. These models were trained for 40 epochs with a batch size of 15.
The model for predicting the winner achieved an accuracy of 65.61 percent, just slightly below the accuracy of other experts in the field of predicting the NBA. The model for predicting total points performed decently as well, it could beat Las Vegas’ prediction 50.04 percent of the time. The model for predicting margin of victory also did well, it beat Las Vegas 50.58 percent of the time.
In order to train the model, data was collected from the NBA statistics website. The model was trained on games dating from the 2010 NBA season through the 2017 NBA season. Three separate models were built, predicting the winner, predicting the total points, and finally predicting the margin of victory for a team. These models learned on 80 percent of the data and validated on the other 20 percent. These models were trained for 40 epochs with a batch size of 15.
The model for predicting the winner achieved an accuracy of 65.61 percent, just slightly below the accuracy of other experts in the field of predicting the NBA. The model for predicting total points performed decently as well, it could beat Las Vegas’ prediction 50.04 percent of the time. The model for predicting margin of victory also did well, it beat Las Vegas 50.58 percent of the time.
ContributorsGarretson, Samuel Burkett (Author) / Meuth, Ryan (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
A common design of multi-agent robotic systems requires a centralized master node, which coordinates the actions of all the agents. The multi-agent system designed in this project enables coordination between the robots and reduces the dependence on a single node in the system. This design change reduces the complexity of the central node, and makes the system more adaptable to changes in its topology. The final goal of this project was to have a group of robots collaboratively claim positions in pre-defined formations, and navigate to the position using pose data transmitted by a localization server.
Planning coordination between robots in a multi-agent system requires each robot to know the position of the other robots. To address this, the localization server tracked visual fiducial markers attached to the robots and relayed their pose to every robot at a rate of 20Hz using the MQTT communication protocol. The robots used this data to inform a potential fields path planning algorithm and navigate to their target position.
This project was unable to address all of the challenges facing true distributed multi-agent coordination and needed to make concessions in order to meet deadlines. Further research would focus on shoring up these deficiencies and developing a more robust system.
Planning coordination between robots in a multi-agent system requires each robot to know the position of the other robots. To address this, the localization server tracked visual fiducial markers attached to the robots and relayed their pose to every robot at a rate of 20Hz using the MQTT communication protocol. The robots used this data to inform a potential fields path planning algorithm and navigate to their target position.
This project was unable to address all of the challenges facing true distributed multi-agent coordination and needed to make concessions in order to meet deadlines. Further research would focus on shoring up these deficiencies and developing a more robust system.
ContributorsThibeault, Quinn (Author) / Meuth, Ryan (Thesis director) / Chen, Yinong (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The nonprofit organization, I Am Zambia, works to give supplemental education to young women in Lusaka. I Am Zambia is creating sustainable change by educating these females, who can then lift their families and communities out of poverty. The ultimate goal of this thesis was to explore and implement high level systematic problem solving through basic and specialized computational thinking curriculum at I Am Zambia in order to give these women an even larger stepping stool into a successful future.
To do this, a 4-week long pilot curriculum was created, implemented, and tested through an optional class at I Am Zambia, available to women who had already graduated from the year-long I Am Zambia Academy program. A total of 18 women ages 18-24 chose to enroll in the course. There were a total of 10 lessons, taught over 20 class period. These lessons covered four main computational thinking frameworks: introduction to computational thinking, algorithmic thinking, pseudocode, and debugging. Knowledge retention was tested through the use of a CS educational tool, QuizIt, created by the CSI Lab of School of Computing, Informatics and Decision Systems Engineering at Arizona State University. Furthermore, pre and post tests were given to assess the successfulness of the curriculum in teaching students the aforementioned concepts. 14 of the 18 students successfully completed the pre and post test.
Limitations of this study and suggestions for how to improve this curriculum in order to extend it into a year long course are also presented at the conclusion of this paper.
To do this, a 4-week long pilot curriculum was created, implemented, and tested through an optional class at I Am Zambia, available to women who had already graduated from the year-long I Am Zambia Academy program. A total of 18 women ages 18-24 chose to enroll in the course. There were a total of 10 lessons, taught over 20 class period. These lessons covered four main computational thinking frameworks: introduction to computational thinking, algorithmic thinking, pseudocode, and debugging. Knowledge retention was tested through the use of a CS educational tool, QuizIt, created by the CSI Lab of School of Computing, Informatics and Decision Systems Engineering at Arizona State University. Furthermore, pre and post tests were given to assess the successfulness of the curriculum in teaching students the aforementioned concepts. 14 of the 18 students successfully completed the pre and post test.
Limitations of this study and suggestions for how to improve this curriculum in order to extend it into a year long course are also presented at the conclusion of this paper.
ContributorsGriffin, Hadley Meryl (Author) / Hsiao, Sharon (Thesis director) / Mutsumi, Nakamura (Committee member) / Arts, Media and Engineering Sch T (Contributor) / Computer Science and Engineering Program (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
DescriptionThe goal of this study is to equip administrators and instructors with a deeper understanding of the apparent cheating problem in Computer Science courses, with proposed solutions to lower academic dishonesty from the students’ perspective.
ContributorsAl Yasari, Farah (Co-author) / Alyasari, Farah (Co-author) / Tadayon-Navabi, Farideh (Thesis director) / Bazzi, Rida (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Spatial audio can be especially useful for directing human attention. However, delivering spatial audio through speakers, rather than headphones that deliver audio directly to the ears, produces the issue of crosstalk, where sounds from each of the two speakers reach the opposite ear, inhibiting the spatialized effect. A research team at Meteor Studio has developed an algorithm called Xblock that solves this issue using a crosstalk cancellation technique. This thesis project expands upon the existing Xblock IoT system by providing a way to test the accuracy of the directionality of sounds generated with spatial audio. More specifically, the objective is to determine whether the usage of Xblock with smart speakers can provide generalized audio localization, which refers to the ability to detect a general direction of where a sound might be coming from. This project also expands upon the existing Xblock technique to integrate voice commands, where users can verbalize the name of a lost item using the phrase, “Find [item]”, and the IoT system will use spatial audio to guide them to it.
ContributorsSong, Lucy (Author) / LiKamWa, Robert (Thesis director) / Berisha, Visar (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
Description
Spatial audio can be especially useful for directing human attention. However, delivering spatial audio through speakers, rather than headphones that deliver audio directly to the ears, produces the issue of crosstalk, where sounds from each of the two speakers reach the opposite ear, inhibiting the spatialized effect. A research team at Meteor Studio has developed an algorithm called Xblock that solves this issue using a crosstalk cancellation technique. This thesis project expands upon the existing Xblock IoT system by providing a way to test the accuracy of the directionality of sounds generated with spatial audio. More specifically, the objective is to determine whether the usage of Xblock with smart speakers can provide generalized audio localization, which refers to the ability to detect a general direction of where a sound might be coming from. This project also expands upon the existing Xblock technique to integrate voice commands, where users can verbalize the name of a lost item using the phrase, “Find [item]”, and the IoT system will use spatial audio to guide them to it.
ContributorsSong, Lucy (Author) / LiKamWa, Robert (Thesis director) / Berisha, Visar (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
Description
Spatial audio can be especially useful for directing human attention. However, delivering spatial audio through speakers, rather than headphones that deliver audio directly to the ears, produces the issue of crosstalk, where sounds from each of the two speakers reach the opposite ear, inhibiting the spatialized effect. A research team at Meteor Studio has developed an algorithm called Xblock that solves this issue using a crosstalk cancellation technique. This thesis project expands upon the existing Xblock IoT system by providing a way to test the accuracy of the directionality of sounds generated with spatial audio. More specifically, the objective is to determine whether the usage of Xblock with smart speakers can provide generalized audio localization, which refers to the ability to detect a general direction of where a sound might be coming from. This project also expands upon the existing Xblock technique to integrate voice commands, where users can verbalize the name of a lost item using the phrase, “Find [item]”, and the IoT system will use spatial audio to guide them to it.
ContributorsSong, Lucy (Author) / LiKamWa, Robert (Thesis director) / Berisha, Visar (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05