Matching Items (6)
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- All Subjects: Creative Project
- All Subjects: Sneakers
Description
We created an Android application, Impromp2, which allows users to search for and save events of interest to them in the Phoenix area. The backend, built on the Parse platform, gathers events daily using Web services and stores them in a database. Impromp2 was designed to improve upon similarly-purposed apps available for Android devices in several key ways, especially in user interface design and data interaction capability. This is a full-stack software project that explores databases and their performance considerations, Web services, user interface design, and the challenges of app development for a mobile platform.
ContributorsNorth, Joseph Robert (Author) / Balasooriya, Janaka (Thesis director) / Nakamura, Mutsumi (Committee member) / Faucon, Philippe (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
For my thesis project, I have developed a cash register web application for the Arizona State University Barrett Dining Hall. I previously worked at the Barrett Dining Hall, and I would occasionally step in as a cashier. This work is how I came to be familiar with the system and all its inefficiencies. The system requires multiple user inputs to implement even the most basic of tasks, is not user-friendly, and therefore very prone to error. In the event that multiple incorrect inputs are entered, the software will freeze, and the user will have to turn off the computer and turn it back on. In theory, this application is an improvement over the software system that is currently in place in that the user interface has been specifically designed to be user-friendly. This application reduces the number of required user inputs by automating certain tasks (such as pricing and determining the meal period), thereby reducing the chance of user error. It is also an improvement in that it allows students to log in to the system to view how many meals they have left, how much M&G is in their account, and how many guest passes they have left. This functionality is extremely important because this is a feature that is not currently in place, and is something that students have actively complained about. Currently, if students want to check on their meal plan, they have to either physically go to a dining hall and ask the cashier, or call a toll-free number. The two technologies used to develop this application are C# and XML. These technologies were chosen because I wanted to learn something new for this project to broaden my knowledge. I also happened to be taking a class at the start of this project that utilized C# and XML for Web Applications, and it seemed like the perfect opportunity to transfer over the skills I had been learning.
ContributorsLewis, Q. Mariha Paishance (Author) / Chen, Yinong (Thesis director) / Nakamura, Mutsumi (Committee member) / School of International Letters and Cultures (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This thesis dives into the world of machine learning by attempting to create an application that will accurately predict whether or not a sneaker will resell at a profit. To begin this study, I first researched different machine learning algorithms to determine which would be best for this project. After ultimately deciding on using an artificial neural network, I then moved on to collecting data, using StockX and Twitter. StockX is a platform where individuals can post and resell shoes, while also providing statistics and analytics about each pair of shoes. I used StockX to retrieve data about the actual shoe, which involved retrieving data for the network feature variables: gender, brand, and retail price. Additionally, I also retrieved the data for the average deadstock price for each shoe, which describes what the mean price of new, unworn shoes are selling for on StockX. This data was used with the retail price data to determine whether or not a shoe has been, on average, selling for a profit. I used Twitter’s API to retrieve links to different shoes on StockX along with retrieving the number of favorites and retweets each of those links had. These metrics were used to account for ‘hype’ of the shoe, with shoes traditionally being more profitable the larger the hype surrounding them. After preprocessing the data, I trained the model using a randomized 80% of the data. On average, the model had about a 65-70% accuracy range when tested with the remaining 20% of the data. Once the model was optimized, I saved it and uploaded it to a web application that took in user input for the five feature variables, tested the datapoint using the model, and outputted the confidence in whether or not the shoe would generate a profit.
From a technical perspective, I used Python for the whole project, while also using HTML/CSS for the front-end of the application. As for key packages, I used Keras, an open source neural network library to build the model; data preprocessing was done using sklearn’s various subpackages. All charts and graphs were done using data visualization libraries matplotlib and seaborn. These charts provided insight as to what the final dataset looked like. They showed how the brand distribution is relatively close to what it should be, while the gender distribution was heavily skewed. Future work on this project would involve expanding the dataset, automating the entirety of the data retrieval process, and finally deploying the project on the cloud for users everywhere to use the application.
From a technical perspective, I used Python for the whole project, while also using HTML/CSS for the front-end of the application. As for key packages, I used Keras, an open source neural network library to build the model; data preprocessing was done using sklearn’s various subpackages. All charts and graphs were done using data visualization libraries matplotlib and seaborn. These charts provided insight as to what the final dataset looked like. They showed how the brand distribution is relatively close to what it should be, while the gender distribution was heavily skewed. Future work on this project would involve expanding the dataset, automating the entirety of the data retrieval process, and finally deploying the project on the cloud for users everywhere to use the application.
ContributorsShah, Shail (Author) / Meuth, Ryan (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
My thesis will revolve around the ideology and sociology of the sneaker brand and it particular, basketball sneakers. The mega sneaker superpower Nike and the under dog of Under Armour have shoes they want to sells and consumers they want to buy them. I will discuss how the advertisement are used and implanted but both Nike and Under Armour. The two points of references from each company will be LeBron James, Nike, and Stephen Curry, Under Armour. Both basketball players have signature shoes and are undoublty the NBAs most relevant players this past season. The two players just so happened to face off against each other in the NBA finals, which enhanced the marketing potential for both companies. Thus, the advertisements for these and their shoes would have been its peak trying sway consumers to either side. Nike and Under Armour both ploy attempts in creating marketing material to attract their consumer base. The Thesis will look at why sneakers have become a social trend and high commodity. I will look at how pop culture and psychological diseases play a roll in the consumers' choice to purchase either shoe. The work as a whole will attempt to bring forth some revitalizing information on today's sneaker culture. Research was limited, however with the information to conduct this thesis, the thesis should spark interest in a new research related field. Thus, bringing forth a new renaissance in today's culture; the Sneaker Life.
ContributorsMitchell, Devon Willie (Author) / Ramsey, Ramsey Eric (Thesis director) / Gruber, Diane (Committee member) / School of Social and Behavioral Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
SmartAid aims to target a small, yet relevant issue in a cost effective, easily replicable, and innovative manner. This paper outlines how to replicate the design and building process to create an intelligent first aid kit. SmartAid utilizes Alexa Voice Service technologies to provide a new and improved way to teach users about the different types of first aid kit items and how to treat minor injuries, step by step. Using Alexa and RaspberryPi, SmartAid was designed as an added attachment to first aid kits. Alexa Services were installed into a RaspberryPi to create a custom Amazon device, and from there, using the Alexa Interaction Model and the Lambda function services, SmartAid was developed. After the designing and coding of the application, a user guide was created to provide users with information on what items are included in the first aid kit, what types of injuries can be treated through first aid, and how to use SmartAid. The
application was tested for its usability and practicality by a small sample of students. Users provided suggestions on how to make the application more versatile and functional, and confirmed that the application made first aid easier and was something that they could see themselves using. While this application is not aimed to replace the current physical guide solution completely, the findings of this project show that SmartAid has potential to stand in as an improved, easy to use, and convenient alternative for first aid guidance.
application was tested for its usability and practicality by a small sample of students. Users provided suggestions on how to make the application more versatile and functional, and confirmed that the application made first aid easier and was something that they could see themselves using. While this application is not aimed to replace the current physical guide solution completely, the findings of this project show that SmartAid has potential to stand in as an improved, easy to use, and convenient alternative for first aid guidance.
ContributorsHasan, Bushra Anwara (Author) / Kobayashi, Yoshihiro (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor) / Department of Psychology (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
It is important for organizations and businesses to have some kind of online presence, as there are enormous benefits, including utilizing the power of web languages to provide services for people. However, creating a website is difficult, and often expensive. While successful businesses can use their profits to develop a costly website, organizations are not so lucky and can't afford to pay large amounts of money for theirs. Thus, the goal of this project was to provide a complete website to the Card Trick Quilters organization found in Show Low, Arizona. The website serves as both a learning experience, to see exactly what it takes to construct a website from the ground up, and a service project that will provide the Card Trick Quilters with a website that performs various services for its members, with functionality that is completely unique to the Arizona quilting community at large. The creation of the website required learning several different skills in regards to web design, such as databases, scripting languages, and even elements of graphic design. The uniqueness of the website comes from the creation of an online submission form for the annual quilt show hosted by the quilters, and an email reminder system where members of the community can submit their addresses and receive emails when there is an upcoming meeting. While there will no doubt be changes and improvements to the website in the future, the website is currently live and ready for the community to use.
ContributorsSchwarting, Jessa Lynn (Author) / Balasooriya, Janaka (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / School of Computing, Informatics, and Decision Systems Engineering (Contributor)
Created2016-05