Matching Items (10)
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- All Subjects: Software Development
- All Subjects: Spotify
- Creators: Balasooriya, Janaka
- Creators: Mazzola, Daniel
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Member of: Theses and Dissertations
Description
As technology's influence pushes every industry to change, healthcare professionals must move to a more connected model. The nearly ubiquitous presence of smartphones presents a unique opportunity for physicians to collect and process data from their patients more frequently. The Mayo Clinic, in partnership with the Barrett Honors College, has designed and developed a prototype smartphone application targeting palliative care patients. The application collects symptom data from the patients and presents it to the doctors. This development project serves as a proof-of-concept for the application, and shows how such an application might look and function. Additionally, the project has revealed significant possibilities for the future of the application.
ContributorsGaney, David Howard (Author) / Balasooriya, Janaka (Thesis director) / Lipinski, Christopher (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
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
This project explores the development of a Ruby on Rails web application to help supervisors manage the tutoring centers at Arizona State University. Each phase of the project's development is examined in detail, including the requirements analysis, system design, system implementation, test strategy, and deployment strategy. The application also includes a REST API for providing the tutoring center data to external applications. These external applications can then present the data, along with their own unique features, to students. This should allow students to have an easier time locating the academic resources they need.
ContributorsRyan, Jay (Author) / Balasooriya, Janaka (Thesis director) / Eaton, John (Committee member) / Walker, Erin (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-12
Description
Web Solutions for Scholastic Tracking is a project which aims to develop a website in order to help the scholarship committee of an Arizona State University sorority save time. Details and flaws of the former approaches to scholastic tracking for the sorority \u2014 such as scattered data, low visibility, and the need for manual calculations \u2014 are provided. Based on these flaws and the requirements of the scholarship committee, a new approach was designed and developed in order to track scholastics online in a more efficient manner. A study hours tracking website was developed utilizing Apache, PHP, and MySQL in order to create an efficient approach to tracking scholastics. The developed website allows sorority members to view their required weekly study hours and submit hours for approval online to specific proctors. The scholarship committee members can then approve or reject the submitted hours that they proctor. This approach has improved the visibility of the required and remaining weekly study hours for each sorority member while also decreasing the time it takes for proctors to approve hours. These improvements serve as examples of the various ways that this project has met its initial goal of increasing the efficiency of the sorority's scholarship program. Additional results as well as the requirements, development approach, technologies used, and testing methods are described in detail throughout this document.
ContributorsKral, Ryan David (Author) / Balasooriya, Janaka (Thesis director) / Burger, Kevin (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2014-05
Description
Fiddlevent is an event searching website written in Ruby on Rails. Fiddlevent enables any person to go online and find local events that interest him. Fiddlevent also enables merchants to post their events online. Fiddlevent explores all challenges of website development, such as project management, database design, user interface design, deployment and the software development lifecycle. Fiddlevent aims to utilize best practices for website and software development.
ContributorsThornton, Christopher Gordon (Author) / Balasooriya, Janaka (Thesis director) / Nakamura, Mutsumi (Committee member) / Hurst, Charles (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
Palliative care is a field that serves to benefit enormously from the introduction of mobile medical applications. Doctors at the Mayo Clinic intend to address a reoccurring dilemma, in which palliative care patients visit the emergency room during situations that are not urgent or life-threatening. Doing so unnecessarily drains the hospital’s resources, and it prevents the patient’s physician from applying specialized care that would better suit the patient’s individual needs. This scenario is detrimental to all involved. A mobile medical application seeks to foster doctor-patient communication while simultaneously decreasing the frequency of these excessive E.R. visits. In order to provide a sufficient standard of usefulness and convenience, the design of such a mobile application must be tailored to accommodate the needs of palliative care patients. Palliative care is focused on establishing long-term comfort for people who are often terminally-ill, elderly, handicapped, or otherwise severely disadvantaged. Therefore, a UI intended for palliative care patients must be devoted to simplicity and ease of use. The application must also be robust enough that the user feels that they have been provided with enough capabilities. The majority of this paper is dedicated to overhauling an existing palliative care application, the product of a previous honors thesis project, and implementing a user interface that establishes a simple, positive, and advantageous environment. This is accomplished through techniques such as color-coding, optimizing page layout, increasing customization capabilities, and more. Above all else, this user interface is intended to make the patient’s experience satisfying and trouble-free. They should be able to log in, navigate the application’s features with a few taps of their finger, and log out — all without undergoing any frustration or difficulties.
ContributorsWilkes, Jarrett Matthew (Co-author) / Ganey, David (Co-author) / Dao, Lelan (Co-author) / Balasooriya, Janaka (Thesis director) / Faucon, Christophe (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Anthemy is a web app that I created so that Spotify users could connect with other uses and see their listening statistics. The app has a chat feature that matches concurrent users based on a variety of search criteria, as well as a statistics page that contains a breakdown of a user's top artists, songs, albums, and genres as well as a detailed breakdown of each of their liked playlists.
ContributorsJackman, Benjamin (Author) / Roumina, Kavous (Thesis director) / Mazzola, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2021-12
ContributorsJackman, Benjamin (Author) / Roumina, Kavous (Thesis director) / Mazzola, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2021-12
ContributorsJackman, Benjamin (Author) / Roumina, Kavous (Thesis director) / Mazzola, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2021-12
Description
Although Spotify’s extensive library of songs are often seen broken up by “Top 100” and main lyrical genres, these categories are primarily based on popularity, artist and general mood alone. If a user wanted to create a playlist based on specific or situationally specific qualifiers from their own downloaded library, he/she would have to hand pick songs that fit the mold and create a new playlist. This is a time consuming process that may not produce the most efficient result due to human error. The objective of this project, therefore, was to develop an application to streamline this process, optimize efficiency, and fill this user need.
Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.
Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.
ContributorsDiMuro, Louis (Author) / Balasooriya, Janaka (Thesis director) / Chen, Yinong (Committee member) / Arts, Media and Engineering Sch T (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05