Matching Items (37)
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- All Subjects: Creative Project
- All Subjects: Python
- Creators: Computer Science and Engineering Program
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
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
An application called "Productivity Heatmap" was created with this project with the goal of allowing users to track how productive they are over the course of a day and week, input through scheduled prompts separated by 30 minutes to 4 hours, depending on preference. The result is a heat map colored according to a user's productivity at particular times of each day during the week. The aim is to allow a user to have a visualization on when he or she is best able to be productive, given that every individual has different habits and life patterns. This application was made completely in Google's Android Studio environment using Java and XML, with SQLite being used for database management. The application runs on any Android device, and was designed to be a balance of providing useful information to a user while maintaining an attractive and intuitive interface. This thesis explores the creation of a functional mobile application for mass distribution, with a particular set of end users in mind, namely college students. Many challenges in the form of learning a new development environment were encountered and overcome, as explained in the report. The application created is a core functionality proof-of-concept of a much larger personal project in creating a versatile and useful mobile application for student use. The principles covered are the creation of a mobile application, meeting requirements specified by others, and investigating the interest generated by such a concept. Beyond this thesis, testing will be done, and future enhancements will be made for mass-market consumption.
ContributorsWeser, Matthew Paul (Author) / Nelson, Brian (Thesis director) / Balasooriya, Janaka (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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
The purpose of this project was to program a Raspberry Pi to be able to play music from both local storage on the Pi and from internet radio stations such as Pandora. The Pi also needs to be able to play various types of file formats, such as mp3 and FLAC. Finally, the project is also to be driven by a mobile app running on a smartphone or tablet. To achieve this, a client server design was employed where the Raspberry Pi acts as the server and the mobile app is the client. The server functionality was achieved using a Python script that listens on a socket and calls various executables that handle the different formats of music being played. The client functionality was achieved by programming an Android app in Java that sends encoded commands to the server, which the server decodes and begins playing the music that command dictates. The designs for both the client and server are easily extensible and allow for any future modifications to the project to be easily made.
ContributorsStorto, Michael Olson (Author) / Burger, Kevin (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
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
Propaganda bots are malicious bots on Twitter that spread divisive opinions and support political accounts. This project is based on detecting propaganda bots on Twitter using machine learning. Once I began to observe patterns within propaganda followers on Twitter, I determined that I could train algorithms to detect these bots. The paper focuses on my development and process of training classifiers and using them to create a user-facing server that performs prediction functions automatically. The learning goals of this project were detailed, the focus of which was to learn some form of machine learning architecture. I needed to learn some aspect of large data handling, as well as being able to maintain these datasets for training use. I also needed to develop a server that would execute these functionalities on command. I wanted to be able to design a full-stack system that allowed me to create every aspect of a user-facing server that can execute predictions using the classifiers that I design.
Throughout this project, I decided on a number of learning goals to consider it a success. I needed to learn how to use the supporting libraries that would help me to design this system. I also learned how to use the Twitter API, as well as create the infrastructure behind it that would allow me to collect large amounts of data for machine learning. I needed to become familiar with common machine learning libraries in Python in order to create the necessary algorithms and pipelines to make predictions based on Twitter data.
This paper details the steps and decisions needed to determine how to collect this data and apply it to machine learning algorithms. I determined how to create labelled data using pre-existing Botometer ratings, and the levels of confidence I needed to label data for training. I use the scikit-learn library to create these algorithms to best detect these bots. I used a number of pre-processing routines to refine the classifiers’ precision, including natural language processing and data analysis techniques. I eventually move to remotely-hosted versions of the system on Amazon web instances to collect larger amounts of data and train more advanced classifiers. This leads to the details of my final implementation of a user-facing server, hosted on AWS and interfacing over Gmail’s IMAP server.
The current and future development of this system is laid out. This includes more advanced classifiers, better data analysis, conversions to third party Twitter data collection systems, and user features. I detail what it is I have learned from this exercise, and what it is I hope to continue working on.
Throughout this project, I decided on a number of learning goals to consider it a success. I needed to learn how to use the supporting libraries that would help me to design this system. I also learned how to use the Twitter API, as well as create the infrastructure behind it that would allow me to collect large amounts of data for machine learning. I needed to become familiar with common machine learning libraries in Python in order to create the necessary algorithms and pipelines to make predictions based on Twitter data.
This paper details the steps and decisions needed to determine how to collect this data and apply it to machine learning algorithms. I determined how to create labelled data using pre-existing Botometer ratings, and the levels of confidence I needed to label data for training. I use the scikit-learn library to create these algorithms to best detect these bots. I used a number of pre-processing routines to refine the classifiers’ precision, including natural language processing and data analysis techniques. I eventually move to remotely-hosted versions of the system on Amazon web instances to collect larger amounts of data and train more advanced classifiers. This leads to the details of my final implementation of a user-facing server, hosted on AWS and interfacing over Gmail’s IMAP server.
The current and future development of this system is laid out. This includes more advanced classifiers, better data analysis, conversions to third party Twitter data collection systems, and user features. I detail what it is I have learned from this exercise, and what it is I hope to continue working on.
ContributorsPeterson, Austin (Author) / Yang, Yezhou (Thesis director) / Sadasivam, Aadhavan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The Tutoring Center Management System is a web-based application for ASU’s University Academic Success Programs (UASP) department, particularly the Math Tutoring Center. It is aimed at providing a user-friendly interface to track queue requests from students visiting the tutoring centers and convert that information into actionable data with the potential to live-track and assess the performance of each tutoring center and each tutor. Numerous UASP processes are streamlined to create an efficient and integrated workflow, such as tutor scheduling, tutor search, shift coverage requests, and analytics. The intended users of the application feature ASU students and the UASP staff, including tutors and supervisors.
ContributorsJain, Prakshal (Co-author) / Gulati, Sachit (Co-author) / Nakamura, Mutsumi (Thesis director) / Selgrad, Justin (Committee member) / Department of Information Systems (Contributor) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-12