Updating search results...

Search Resources

5 Results

View
Selected filters:
Complex Networks and Graphs
Read the Fine Print
Educational Use
Rating
0.0 stars

Students learn about complex networks and how to represent them using graphs. They also learn that graph theory is a useful mathematical tool for studying complex networks in diverse applications of science and engineering, such as neural networks in the brain, biochemical reaction networks in cells, communication networks, such as the internet, and social networks. Topics covered include set theory, defining a graph, as well as defining the degree of a node and the degree distribution of a graph.

Subject:
Engineering and Information Technologies
Material Type:
Lesson Plan
Provider:
TeachEngineering
Provider Set:
TeachEngineering
Author:
Debbie Jenkinson
Garrett Jenkinson
John Goutsias
Susan Frennesson
Date Added:
09/18/2014
Curb the Epidemic!
Read the Fine Print
Educational Use
Rating
0.0 stars

Using a website simulation tool, students build on their understanding of random processes on networks to interact with the graph of a social network of individuals and simulate the spread of a disease. They decide which two individuals on the network are the best to vaccinate in an attempt to minimize the number of people infected and "curb the epidemic." Since the results are random, they run multiple simulations and compute the average number of infected individuals before analyzing the results and assessing the effectiveness of their vaccination strategies.

Subject:
Engineering and Information Technologies
Health Science Technologies
Material Type:
Activity/Lab
Provider:
TeachEngineering
Provider Set:
TeachEngineering
Author:
Debbie Jenkinson
Garrett Jenkinson
John Goutsias
Susan Frennesson
Date Added:
09/18/2014
It's a Connected World: The Beauty of Network Science
Read the Fine Print
Educational Use
Rating
0.0 stars

Students learn about complex networks and how to use graphs to represent them. They also learn that graph theory is a useful part of mathematics for studying complex networks in diverse applications of science and engineering, including neural networks in the brain, biochemical reaction networks in cells, communication networks, such as the internet, and social networks. Students are also introduced to random processes on networks. An illustrative example shows how a random process can be used to represent the spread of an infectious disease, such as the flu, on a social network of students, and demonstrates how scientists and engineers use mathematics and computers to model and simulate random processes on complex networks for the purposes of learning more about our world and creating solutions to improve our health, happiness and safety.

Subject:
Engineering and Information Technologies
Material Type:
Unit of Study
Provider:
TeachEngineering
Provider Set:
TeachEngineering
Author:
Debbie Jenkinson
Garrett Jenkinson
John Goutsias
Susan Frennesson
Date Added:
09/18/2014
Processes on Complex Networks
Read the Fine Print
Educational Use
Rating
0.0 stars

Building on their understanding of graphs, students are introduced to random processes on networks. They walk through an illustrative example to see how a random process can be used to represent the spread of an infectious disease, such as the flu, on a social network of students. This demonstrates how scientists and engineers use mathematics to model and simulate random processes on complex networks. Topics covered include random processes and modeling disease spread, specifically the SIR (susceptible, infectious, resistant) model.

Subject:
Engineering and Information Technologies
Life Science
Mathematics
Material Type:
Lesson Plan
Provider:
TeachEngineering
Provider Set:
TeachEngineering
Author:
Debbie Jenkinson
Garrett Jenkinson
John Goutsias
Susan Frennesson
Date Added:
09/18/2014
Start Networking!
Read the Fine Print
Educational Use
Rating
0.0 stars

To get a better understanding of complex networks, students create their own, real social network example by interacting with their peers in the classroom and documenting the interactions. They represent the interaction data as a graph, calculate two mathematical quantities associated with the graph—the degree of each node and the degree distribution of the graph—and analyze how these quantities can be used to infer properties of the social network at hand.

Subject:
Engineering and Information Technologies
Mathematics
Material Type:
Activity/Lab
Provider:
TeachEngineering
Provider Set:
TeachEngineering
Author:
Debbie Jenkinson
Garrett Jenkinson
John Goutsias
Susan Frennesson
Date Added:
09/18/2014