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- Creators: Computer Science and Engineering Program
Description
This project explores how modern mobile technology can be used to provide support for domestic violence victims. The goal of the project is to create a proof-of-concept iOS mobile application that maintains a discreet safety front and provides domestic violence victims with resources and safety planning. The design and implementation are disguised as a hair salon app to maintain a low profile on the user’s phone. The HairHelp app features quick exit navigation, a secure database to store a user’s private and personal documents in case of emergency, and a checklist of safety planning measures. The steps taken in this project serve as the foundation for a larger project in the long term.
ContributorsShovkovy, Sophia (Author) / Balasooriya, Janaka (Thesis director) / Wilkey, Douglas (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
HackerHero is an educational game designed to teach children, especially those from marginalized backgrounds, computation thinking skills needed for STEAM fields. It also teaches children about social injustice. This project was focused on creating an audio visualization for an AI character within the HackerHero game. The audio visualization consisted of a static silhouette of a face and a wave-like form to represent the mouth. Audio content analysis was performed on audio sampled from the character’s voice lines. Pitch and amplitude derived from the analysis was used to animate the character’s visual features such as it’s brightness, color, and mouth movement. The mouth’s movement and color was manipulated with the audio’s pitch. The lights of Wave were controlled by the amplitude of the audio. Design considerations were made to accommodate those with visual disabilities such as color blindness and epilepsy. Overall the final audio visualization satisfied the project sponsor and built upon existing audio visualization work. User feedback will be a necessity for improving the audio visualization in the future.
ContributorsNguyen, Joshep D (Author) / Chavez-Echaegaray, Helen (Thesis director) / Waggoner, Trae (Committee member) / Department of Psychology (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
A primary goal in computer science is to develop autonomous systems. Usually, we provide computers with tasks and rules for completing those tasks, but what if we could extend this type of system to physical technology as well? In the field of programmable matter, researchers are tasked with developing synthetic materials that can change their physical properties \u2014 such as color, density, and even shape \u2014 based on predefined rules or continuous, autonomous collection of input. In this research, we are most interested in particles that can perform computations, bond with other particles, and move. In this paper, we provide a theoretical particle model that can be used to simulate the performance of such physical particle systems, as well as an algorithm to perform expansion, wherein these particles can be used to enclose spaces or even objects.
ContributorsLaff, Miles (Author) / Richa, Andrea (Thesis director) / Bazzi, Rida (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
Investment real estate is unique among similar financial instruments by nature of each property's internal complexities and interaction with the external economy. Where a majority of tradable assets are static goods within a dynamic market, real estate investments are dynamic goods within a dynamic market. Furthermore, investment real estate, particularly commercial properties, not only interacts with the surrounding economy, it reflects it. Alive with tenancy, each and every commercial investment property provides a microeconomic view of businesses that make up the local economy. Management of commercial investment real estate captures this economic snapshot in a unique abundance of untapped statistical data. While analysis of such data is undeniably valuable, the efforts involved with this process are time consuming. Given this unutilized potential our team has develop proprietary software to analyze this data and communicate the results automatically though and easy to use interface. We have worked with a local real estate property management and ownership firm, Reliance Management, to develop this system through the use of their current, historical, and future data. Our team has also built a relationship with the executives of Reliance Management to review functionality and pertinence of the system we have dubbed, Reliance Dashboard.
ContributorsBurton, Daryl (Co-author) / Workman, Jack (Co-author) / LePine, Marcie (Thesis director) / Atkinson, Robert (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Management (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
MeetPoint is a project derived from Computer Science with a focus upon applications to mobile. The application is created to provide users with the ability to meet up with certain individuals to accomplish a specific task, in this case studying. The project idea came from the creator wanting to meet up with a friend in order to converse about an upcoming exam. The creator knew where the person lived, but could not easily come up with a location for the two to meet that would be a reasonable distance from both of them. Hence came the idea for a mobile application to complete those actions for the user. The project focuses upon implementation in a school setting in which the meetings would actually take place. For means of this project, the locations were fixed to on campus at Arizona State University. The committee felt that this would scope the project correctly for its two-semester creation while still demonstrating how to fulfill the task at hand. Android is the operating system of choice for the mobile application due to it being Java, which was the most familiar language to the student. MeetPoint provides users with an easy to navigate and familiar front-end while harnessing the power of a database in the back-end. The application hides the intricacies of the back-end from the user in order to better provide a comfortable user experience. A lot of the project was designed around providing a comfortable user experience by keeping the application familiar to the user in that it maintains similarities with other popular mobile applications.
ContributorsWallace, Tyler L (Author) / Balasooriya, Janaka (Thesis director) / Faucon, Christophe (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
The objective of this research is to determine an approach for automating the learning of the initial lexicon used in translating natural language sentences to their formal knowledge representations based on lambda-calculus expressions. Using a universal knowledge representation and its associated parser, this research attempts to use word alignment techniques to align natural language sentences to the linearized parses of their associated knowledge representations in order to learn the meanings of individual words. The work includes proposing and analyzing an approach that can be used to learn some of the initial lexicon.
ContributorsBaldwin, Amy Lynn (Author) / Baral, Chitta (Thesis director) / Vo, Nguyen (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot detection, we are interested in bots on Twitter that tweet Arabic extremist-like phrases. A testing dataset is collected using the honeypot method, and five different heuristics are measured for their effectiveness in detecting bots. The model underperformed, but we have laid the ground-work for a vastly untapped focus on bot detection: extremist ideal diffusion through bots.
ContributorsKarlsrud, Mark C. (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
Cyber threats are growing in number and sophistication making it important to continually study and improve all dimensions of digital forensics. Teamwork in forensic analysis has been overlooked in systems even though forensics relies on collaboration. Forensic analysis lacks a system that is flexible and available on different electronic devices which are being used and incorporated into everyday life. For instance, cellphones or tablets that are easy to bring on-the-go to sites where the first steps of forensic analysis is done. Due to the present day conversion to online accessibility, most electronic devices connect to the internet. Squeegee is a proof of concept that forensic analysis can be done on the web. The forensic analysis expansion to the web opens many doors to collaboration and accessibility.
ContributorsJuntiff, Samantha Maria (Author) / Ahn, Gail-Joon (Thesis director) / Kashiwagi, Jacob (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
Bhairavi is a solo performance that investigates belonging and dis-belonging in diaspora communities, especially as it relates to the female body. Specifically, through my experience as a second-generation Indian-American woman - I expose and challenge the notion of ‘tradition,’ as it is forced into women’s bodies, and displaces them in their own homes. Bhairavi is a story told through movement and theatrical narrative composition with research and material collected through structured and unstructured observation of my family, cultural community, and myself.
Note: This work of creative scholarship is rooted in collaboration between three female artist-scholars: Carly Bates, Raji Ganesan, and Allyson Yoder. Working from a common intersectional, feminist framework, we served as artistic co-directors of each other’s solo pieces and co-producers of Negotiations, in which we share these pieces in relationship to each other. Thus, Negotiations is not a showcase of three individual works, but rather a conversation among three voices. As collaborators, we have been uncompromising in the pursuit of our own unique inquiries and voices, and each of our works of creative scholarship stand alone. However, we believe that all of the parts are best understood in relationship to each other, and to the whole. For this reason, we have chosen to cross-reference our thesis documents.
French Vanilla: An Exploration of Biracial Identity Through Narrative Performance by Carly Bates
Deep roots, shared fruits: Emergent creative process and the ecology of solo performance through “Dress in Something Plain and Dark” by Allyson Yoder
Bhairavi: A Performance-Investigation of Belonging and Dis-Belonging in Diaspora
Communities by Raji Ganesan
Note: This work of creative scholarship is rooted in collaboration between three female artist-scholars: Carly Bates, Raji Ganesan, and Allyson Yoder. Working from a common intersectional, feminist framework, we served as artistic co-directors of each other’s solo pieces and co-producers of Negotiations, in which we share these pieces in relationship to each other. Thus, Negotiations is not a showcase of three individual works, but rather a conversation among three voices. As collaborators, we have been uncompromising in the pursuit of our own unique inquiries and voices, and each of our works of creative scholarship stand alone. However, we believe that all of the parts are best understood in relationship to each other, and to the whole. For this reason, we have chosen to cross-reference our thesis documents.
French Vanilla: An Exploration of Biracial Identity Through Narrative Performance by Carly Bates
Deep roots, shared fruits: Emergent creative process and the ecology of solo performance through “Dress in Something Plain and Dark” by Allyson Yoder
Bhairavi: A Performance-Investigation of Belonging and Dis-Belonging in Diaspora
Communities by Raji Ganesan
ContributorsGanesan, Raji J (Author) / Underiner, Tamara (Thesis director) / Stephens, Mary (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This paper presents work that was done to create a system capable of facial expression recognition (FER) using deep convolutional neural networks (CNNs) and test multiple configurations and methods. CNNs are able to extract powerful information about an image using multiple layers of generic feature detectors. The extracted information can be used to understand the image better through recognizing different features present within the image. Deep CNNs, however, require training sets that can be larger than a million pictures in order to fine tune their feature detectors. For the case of facial expression datasets, none of these large datasets are available. Due to this limited availability of data required to train a new CNN, the idea of using naïve domain adaptation is explored. Instead of creating and using a new CNN trained specifically to extract features related to FER, a previously trained CNN originally trained for another computer vision task is used. Work for this research involved creating a system that can run a CNN, can extract feature vectors from the CNN, and can classify these extracted features. Once this system was built, different aspects of the system were tested and tuned. These aspects include the pre-trained CNN that was used, the layer from which features were extracted, normalization used on input images, and training data for the classifier. Once properly tuned, the created system returned results more accurate than previous attempts on facial expression recognition. Based on these positive results, naïve domain adaptation is shown to successfully leverage advantages of deep CNNs for facial expression recognition.
ContributorsEusebio, Jose Miguel Ang (Author) / Panchanathan, Sethuraman (Thesis director) / McDaniel, Troy (Committee member) / Venkateswara, Hemanth (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05