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An Analysis of Healthcare Capital Equipment Planning and Healthcare Software Implementation

Description

Healthcare facilities are essential for any community, and they must stay up-to-date with the latest equipment and technology. They provide necessary resources for keeping populations healthy and safe. In order to provide healthcare services, these healthcare facilities must be adequately equipped with appropriate physical capital as well as software to…

Healthcare facilities are essential for any community, and they must stay up-to-date with the latest equipment and technology. They provide necessary resources for keeping populations healthy and safe. In order to provide healthcare services, these healthcare facilities must be adequately equipped with appropriate physical capital as well as software to meet the demands of their patients. Healthcare capital equipment planning involves building up a facility with all it’s equipment and is a part of the healthcare supply chain. Attainia is a healthcare capital equipment planning software used to assist equipment planners in organizing the procurement of equipment for their projects. Attainia has a large amount of data about the capital equipment supply chain through the Attainia equipment catalog. Analysis of this catalog data reveals different patterns in the spending patterns of capital equipment planners as well as trends in the supplier offerings. Since Attainia itself is a software, Attainia’s users have experience with implementing and integrating software into healthcare IT solutions. Their experiences give some insight into the complex nature of software implementations at healthcare facilities. The COVID-19 pandemic has affected healthcare facilities all over the world. Impacting the supply chain and hitting hospitals’ finances, COVID-19 has drastically changed many parts of the healthcare system. This paper will examine some of these ongoing effects from COVID-19 along with analysis on capital equipment planning, supply chain, and healthcare software implementation.
ContributorsShah, Shailee (Author) / Pye, Jessica (Thesis director) / Roumina, Kavous (Committee member) / School of International Letters and Cultures (Contributor) / Department of Information Systems (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Song Sift: Angular Web App to Filter Songs and Create Customizable Playlists via the Spotify API

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,…

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.
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

Creating a Web Application to Connect Spotify Users With Similar Music Tastes

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…

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
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Jackman Final Project

ContributorsJackman, Benjamin (Author) / Roumina, Kavous (Thesis director) / Mazzola, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2021-12
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Anthemy Source Code

ContributorsJackman, Benjamin (Author) / Roumina, Kavous (Thesis director) / Mazzola, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2021-12