Matching Items (3)
Filtering by
- Creators: Barrett, The Honors College
- Creators: Church, Kathy
Description
This report details a prioritization value model that was created for the use of Arizona State University and ASU LightWorks in determining and implementing appropriate sustainability projects for removing greenhouse gas emissions. A thorough review regarding the current project selection process, and an extensive analysis into the desired state of the process was conducted for this paper. The newly developed prioritization model includes multiple attributes that rank and prioritize projects based upon the highest value as determined by criteria set forth by the university. Encompassed within this report are the steps in creating the decision model, as well as the benefits and additional uses of the model for the end user. From the analysis and model created, the end user has the ability to choose carbon neutral projects that better align with the vision of the New American University.
ContributorsAmoroso, Nicholas (Co-author) / Lee, Betty (Co-author) / Brooks, Dan (Thesis director) / Johnson, Travis (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor)
Created2015-05
Description
Charlie Arntzen joined ASU in August 2000 as the Florence Ely Nelson Presidential Endowed Chair and retired in 2016 from the School of Life Sciences and Biodesign Institute. Charlie was the founding Director of the Biodesign Institute.
Important ASU stories include:
1) the creation of the Biodesign Institute,
2) the design and operation of the Biodesign labs,
3) the development of ZMapp to fight Ebola,
4) The New American University - a discussion of the importance of collaboration, and
5) several comments about Presidents Coor and Crow and Provost Glick
ContributorsChurch, Kathy (Interviewer) / Arizona State University Retirees Association (Producer)
Created2019-05-08
Description
A mobile phone application was designed as part of an X-Prize challenge at Arizona State University (ASU). The team created an application that displays 4D visualization of time sensitive contagion data, specifically focusing on the Ebola Virus Disease. The application, named “Ebola Resource Decision Evaluator” (ERDE), is a tool to aid in resource allocation for decision-makers during epidemics and outbreaks. The predictive algorithm was based on the SIR Model—susceptible, infected, and recovered (or immune). We adapted this predictive model into our application to forecast weeks forward the Ebola incidence in three cities in the Democratic Republic of Congo (DRC).
The current 2D map used by the Center for Disease Control (CDC) displays only the number of deaths in a city caused by the outbreak. But, the cities differ in ways 2D cannot convey. We implemented the augmented reality (AR) aspect to give more meaning to data and to give decision-makers interactive 4D city-by-city comparisons. The outbreak is ongoing as of September 2019 and ASU has committed to hosting the application for other healthcare workers to use. The application incorporates the most recent data on the disease and updates to visualize how many are predicted to become infected given X units of vaccine. We are able to use the data and compare the effectiveness to other cities. After this collection of data, professionals would determine the most efficient action to take against the spread of the disease.
The current 2D map used by the Center for Disease Control (CDC) displays only the number of deaths in a city caused by the outbreak. But, the cities differ in ways 2D cannot convey. We implemented the augmented reality (AR) aspect to give more meaning to data and to give decision-makers interactive 4D city-by-city comparisons. The outbreak is ongoing as of September 2019 and ASU has committed to hosting the application for other healthcare workers to use. The application incorporates the most recent data on the disease and updates to visualize how many are predicted to become infected given X units of vaccine. We are able to use the data and compare the effectiveness to other cities. After this collection of data, professionals would determine the most efficient action to take against the spread of the disease.
ContributorsHu, Lawrence (Author) / Hall, Rick (Thesis director) / Johnson-Glenberg, Mina (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / Edson College of Nursing and Health Innovation (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05