Joint CS4760, CS5760 & HU4628 Scientists and App Ideas
Below is the list of scientists and their potential applications for collaborative CS4760, CS5760 & HU4628 teams.
Bill Siever – Principle Lecturer
Contact Information
Email: bsiever at wustl.edu
Phone: (573) 364-8890
https://cse.wustl.edu/faculty/Pages/Bill-Siever.aspx
Computer Science
Washington University in St. Louis
App Idea: Microbit App
The micro:bit is a low-cost hardware platform that is used to introduce both computer programming principles and to facilitate maker activities, like making wearables. It’s already widely used by K-12 educators for computing activities, but, due to it on-board sensors and its extensibility, it’s could also augment classroom science demonstrations. (For example, the existing Makecode editor already can be used to collect and graph streaming data. See here for a simulated micro:bit graphing accelerometer data. Click the Edit button, then click the Show console Simulator button. The micro:bit shown as a rectangle with buttons and gold connectors at the bottom. Moving over the image of the micro:bit will simulate tilting and the graphed data)
The Makecode simulator can already collect and graph data, but it’s data collection window can only graph a small sample of data and it’s limited to just one micro:bit at a time. The goal of this project is to develop a stand-alone web site that will collect information from one or more micro:bits and allow users to graph a wider range of data and interact with the data in ways not supported by Makecode.
Initial Meetings
First Team-Scientist Meeting: Monday, Jan. 27, at 6:30 pm EDT (5:30 pm CDT)
Second Team-Scientist Meeting: Thursday, Jan. 30, at 4:00 pm EDT (3:00 pm CDT)
Prefer to use Zoom for meetings.
Erich Petushek – Assistant Professor, Applied Cognitive Science and Human Factors
Contact Information
Email: ejpetush at mtu.edu
Phone: (906) 487-3204
https://www.mtu.edu/cls/people/faculty-allied-content/petushek/
Cognitive and Learning Sciences
Harold Meese 207
Michigan Technological University
App Idea: ACL Injury Risk Calculator
Approximately 40 million school-aged children (5-18 yrs) in the United State participate in sports, a vital component to fostering long-term health and well-being. However, sports accidents are the second most common and costly cause of severe injury in pediatric populations, accounting for $2 billion in healthcare costs annually. Knee injuries such as anterior cruciate ligament (ACL) injuries are the most common, severe and season/career ending sport injury, the majority of which can be prevented. However, no formal clinical tool is available to estimate risk. This app will allow individuals to estimate their injury risk based on various simple demographic factors such as age, sex, sport type, and previous injury. The results will be displayed in an easy to understand format to foster motivation to engage in prevention activities if risk estimates are high.
Initial Meetings
First Team-Scientist Meeting: Thursday, Jan. 23, at 3:30 pm
Second Team-Scientist Meeting: Thursday, Jan. 30 at 3:30 pm
Prefer in person at Harold Meese 206
Angie Carter – Assistant Professor, Environmental/Energy Justice
Contact Information
Email: ancarter at mtu.edu
Office Phone: (906) 487-1431
https://www.mtu.edu/social-sciences/department/faculty/carter/
Social Sciences
Academic Office Building 207
Michigan Technological University
App Idea: Backyard Berry
An app for berry pickers to record harvests and to learn more about the diversity of berries in Great Lakes region, and for scientists to learn about harvest and demographics of berry pickers
This citizen science app will collect preliminary data about recreational berry picking and foraging across the region. Berry picking is an important cultural and economic activity across the Great Lakes region and supports a variety of local value-added products and agritourism, such as products made from jams and visits to u-pick farms. The app will collect self-reported data from berry pickers about their berry harvests, cultural uses of berries, as well as demographic information about the berry pickers. Additionally, the harvest data will populate a map that shows users where and when berries are being picked. This information is especially of interest to the research team because of the presence across the region of spotted wing drosophila (SWD, Drosophila suzukii, Diptera: Drosophilidae), an invasive fruit fly originating from South-east Asia that is a major pest of soft-skinned fruits worldwide such as blueberries, cherries, raspberries, and strawberries. Developing larvae inside the berries can render berries unmarketable and rapidly reduce processed fruit quality, but little is known about its influence upon berries in forested areas or wild berries. This is a concern to the biodiversity of the region because the Great Lakes region is home to the original cultivars of many commercial fruits grown today around the world; SWD poses a significant risk to the sustainability of these important plants. We are interested in how SWD may affect the health of berries as well as its potential impact upon social, cultural, and economic systems.The app users will gain information about how to identify different types of berries, how to test for the presence of the fruit fly through a simple home test, and be able to see where others are finding berries throughout the region. Our hope is that users will learn more about the diversity of berries in the region and better understand the importance of protecting them from harm. If all goes well in development, we will pilot the app in summer 2020 with a focus group of local foragers.
Initial Meetings
First Team-Scientist Meeting: Thursday, Jan. 23 at 3:30 pm
Second Team-Scientist Meeting: Thursday, Jan 30 at 3:30 pm
Prefer in person at AOB 201
Don LaFreniere – Assistant Professor of Historical Geography and GIS & Sarah Scarlett – Assistant Professor of History
Contact Information
Email: djlafren at mtu.edu & sfscarle at mtu.edu
Office Phone: 906-487-2189
http://www.keweenawhistory.com/
Office: AOB 200A, GLRC 208
Lab: GLRC 316
Social Science Department
Michigan Technological University
App Idea: Keweenaw Time Traveler Story Query Tool
The Keweenaw Time Traveler is a historic spatial data infrastructure (HSDI)that is recreating the built and social environments of the Copper Country from 1850 to 1950. Every ten years, corresponding with the decennial census, we are mapping and modelling in all of the houses, businesses, schools, and copper mining sites. Individual level socio-demographic information is mapped to each structure, allowing us to know where every individual lived, worked, and went to school in the Keweenaw for a hundred year period. Core to the project is the ‘Explore App’, which allows the public to explore the datasets and contribute their own knowledge about the region with spatial-temporally located text, photos, and videos. At present, all stories are viewable on the maps at once. Next next step is to construct a query tool that will allow users to filter the stories into themes and display them interactively on the map. This functionality will use the basemaps and data already created and will need to make calls directly into HSDI database via our API and PHP endpoints.
Initial Meetings
First Team-Scientist Meeting: Thursday 1/23/2020 at 3:30 pm
Second Team-Scientist Meeting: Thursday 1/30/2020 at 3:30 pm
Meet in person at GLRC 316.
Erin Johnston – Wildlife Biologist
Contact Information
Email:ejohnston at kbic-nsn.gov
Office Phone: (906) 524-5757 ext 20
Office:
Keweenan Bay Indian Community Natural Resource Department
14359 Pequaming Road
L’Anse, MI 49946
App Idea: A Guide to Fishing in the Western Upper Peninsula of Michigan
The Western Upper Peninsula of Michigan (WUP) is a popular destination for fishermen and women and is home to the Keweenaw Bay Indian Community (KBIC). KBIC’s traditional territory is composed of several hundred inland lakes and thousands of miles of rivers, streams, and creeks. Fishing in Keweenaw Bay has a lineage centuries long and forms the foundation for cultural beliefs and values, traditional lifeways, and even individual identity.
If you are new to the area or to fishing, you may not know exactly where to fish, which species to pursue, or which rules and regulations apply to you (Federal, Tribal, and/or State). This app will provide users the ability to find information about WUP water bodies including popular access points, season regulations and size limits, stocking information, fish consumption advisories, and more.
Initial Meetings
First Team-Scientist Meeting: Thursday, Jan 23 at 3:30 pm
Second Team-Scientist Meeting: Thursday, Jan 30 at 3:30 pm
Prefer by Zoom.
Kuilin Zhang – Associate Professor of Transportation
Contact Information
Email: klzhang at mtu.edu
Phone/Text: 906-487-1828
https://sites.google.com/site/zhangmichigantech/
Office: Dillman 301i
Civil and Environmental Engineering
Michigan Technological University
App Idea: App for Demonstrating Algorithms to Solve Routing Games of Connected and Automated Vehicles
Vehicle connectivity and automation technologies will revolutionize highway transportation systems. Self-driving cars are enabled to automatically make driving decisions such as accelerating, braking, and steering relying on sensing technologies and machine learning algorithms. However, the fully self-driving cars (with no steering wheel, no pedal, and no driver) require a mechanism to automatically make routing decisions to respond to traffic uncertainty in the highway transportation networks. The advance of vehicular wireless communication technologies such as C-V2X (Cellular vehicle-to-everything) and DSRC (Dedicated Short-Range Communications) enable a connected vehicular ad-hoc network (VANET) to share real-time information, which can be used to make automated routing decisions in response to uncertainty traffic events that can reduce travel time and decrease energy consumption for connected and automated vehicles (CAVs). This app will show the automated routing mechanism of connected and automated vehicles (CAVs) from their origins and destinations in the transportation network with real-time information based on the congestion game theory, which can achieve a Nash equilibrium such that no CAV can unilaterally change routes to improve their travel times. With a given transportation network (with some link performance functions to model traffic congestion) and a set of CAV agents (from various origins to various destinations), this app can demonstrate the mechanism of algorithms to solve the routing games step-by-step for each CAV agent iteration-by-iteration to reach a Nash equilibrium solution. This app will be used in a course in transportation such that students (with each student to be assumed as a CAV agent) can learn the routing game algorithms via class interactions and visualizations.
Initial Meetings
First Team-Scientist Meeting: Thursday, January 23 at 3:30 pm
Second Team-Scientist Meeting: January 30 at 3:30 pm
Prefer in person at Dillman 301j.