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Description
A defense-by-randomization framework is proposed as an effective defense mechanism against different types of adversarial attacks on neural networks. Experiments were conducted by selecting a combination of differently constructed image classification neural networks to observe which combinations applied to this framework were most effective in maximizing classification accuracy. Furthermore, the

A defense-by-randomization framework is proposed as an effective defense mechanism against different types of adversarial attacks on neural networks. Experiments were conducted by selecting a combination of differently constructed image classification neural networks to observe which combinations applied to this framework were most effective in maximizing classification accuracy. Furthermore, the reasons why particular combinations were more effective than others is explored.
ContributorsMazboudi, Yassine Ahmad (Author) / Yang, Yezhou (Thesis director) / Ren, Yi (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
This study aims to examine how the use of consensus-based transactions, smart contracts,and interoperability, provided by blockchain, may benefit the blood plasma industry. Plasmafractionation is the process of separating blood into multiple components to garner benefitsof increased lifespan, specialized allocation, and decreased waste, thereby creating a morecomplex and flexible supply

This study aims to examine how the use of consensus-based transactions, smart contracts,and interoperability, provided by blockchain, may benefit the blood plasma industry. Plasmafractionation is the process of separating blood into multiple components to garner benefitsof increased lifespan, specialized allocation, and decreased waste, thereby creating a morecomplex and flexible supply chain. Traditional applications of blockchain are developed onthe basis of decentralization—an infeasible policy for this sector due to stringent governmentregulations, such as HIPAA. However, the trusted nature of the relations in the plasmaindustry’s taxonomy proves private and centralized blockchains as the viable alternative.Implementations of blockchain are widely seen across pharmaceutical supply chains to combatthe falsification of possibly afflictive drugs. This system is more difficult to manage withblood, due to the quick perishable time, tracking/tracing of recycled components, and thenecessity of real-time metrics. Key attributes of private blockchains, such as digital identity,smart contracts, and authorized ledgers, may have the possibility of providing a significantpositive impact on the allocation and management functions of blood banks. Herein, we willidentify the economy and risks of the plasma ecosystem to extrapolate specific applications forthe use of blockchain technology. To understand tangible effects of blockchain, we developeda proof of concept application, aiming to emulate the business logic of modern plasma supplychain ecosystems adopting a blockchain data structure. The application testing simulates thesupply chain via agent-based modeling to analyze the scalability, benefits, and limitations ofblockchain for the plasma fractionation industry.
ContributorsVallabhaneni, Saipavan K (Author) / Boscovic, Dragan (Thesis director) / Kellso, James (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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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
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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

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
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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

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
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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

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.
Created2019-05
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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

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.
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
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Description
ASU’s Software Engineering (SER) program adequately prepares students for what happens after they become a developer, but there is no standard for preparing students to secure a job post-graduation in the first place. This project creates and executes a supplemental curriculum to prepare students for the technical interview process. The

ASU’s Software Engineering (SER) program adequately prepares students for what happens after they become a developer, but there is no standard for preparing students to secure a job post-graduation in the first place. This project creates and executes a supplemental curriculum to prepare students for the technical interview process. The trial run of the curriculum was received positively by study participants, who experienced an increase in confidence over the duration of the workshop.
ContributorsSchmidt, Julia J (Author) / Roscoe, Rod (Thesis director) / Bansal, Srividya (Committee member) / Software Engineering (Contributor) / Human Systems Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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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
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Description

In the United States, the word "earthquake" is extensively used. This natural disaster has a year-round impact on numerous states across the country. Earthquakes are simply more than a natural calamity; they also have a negative psychological impact. Earthquake safety measures are essential for ensuring citizens' safety. This paper proposes,

In the United States, the word "earthquake" is extensively used. This natural disaster has a year-round impact on numerous states across the country. Earthquakes are simply more than a natural calamity; they also have a negative psychological impact. Earthquake safety measures are essential for ensuring citizens' safety. This paper proposes, a technique for evaluating earthquake safety activities and instructing individuals in selecting appropriate precautions. Earthquake protection using Reach.love plus Amazon Alexa is special in that it uses cutting-edge virtual reality technology. The platform developed by Reach.love takes earthquake prevention to a new and innovative direction. The feeling of presence in a VR headset linked within Reach.love, allows the user to feel that an earthquake is occurring right now. Additionally, each location includes audio instructions that explain what to do in specific scenarios. The user can practice and mentally train to respond appropriately when a real earthquake happens, comparable to a 3D drill. Finally, the user will be able to utilize Amazon Alexa for help within the rooms in Reach.love to improve the experience of earthquake safety training. For example, if the user speaks to Alexa during the simulation and says, "Alexa, turn off the audio instructions," Alexa will do so, and the user will no longer hear them. Alexa would be the user's personal assistant during the training of earthquake protection.

ContributorsKaur, Simran (Author) / Johnson, Mina (Thesis director) / de la Pena, Nonny (Committee member) / Barrett, The Honors College (Contributor) / Computer Science - BS (Contributor)
Created2022-05