Lake Superior State University
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"It seems like the more people I talk to, the more I realize just how good of an engineering program LSSU has. I appreciate your classes, your ability to make learning an enjoyable experience, and the hands-on attitude of LSSU as a whole. I am very glad I chose LSSU."

Jake Weinmann Controls Engineer, ADD Software/Fanuc Robotics

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Senior projects students meet with their faculty advisors and project customers to review designs and proposals.


Senior Projects 2006-07

Computer Controlled Plasma Designs (CCPD)

Phase II of a robotic plasma cutter
Customer:
Lake Superior State University

Robotic Calibration Systems (RCS)

Robot steering calibrator stand
Customer:
Continental Automotive Systems, Inc.

Superior Drivetrain Solutions (SDS)

SAE Mini Baja Competition - Drivetrain
Customer: Lake Superior State University

Specialized Testing Systems (STS)

Trailer beam tester
Customer: Algoma Steel-Essar

Twisted Off Road Chassis (TORC)

SAE Mini Baja Competition - Chassis
Customer:
Lake Superior State University

Universal Signal Routing (USR)

Universal steering column validator
Customer:
DELPHI

 

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Engineering Jobs

 

 

 

A Spatial Analysis of Greenhouse Gasses and Household Income

Scott Sowers

Emissions of greenhouse gases (GHG) by industries have been increasing at an exponential rate in the past century. As these emissions increase in number of sources, as well as amount of output, the impact on the environment becomes more significant. However, the United States relies heavily on industry for creation of new products, materials, and economic factors such as employment. Industries attract employment opportunities, which in return attract living accommodations. The basis of this project was to see if there is any spatial correlation between GHG emissions and income of households (within a county) of a GHG emitter. Using Geographical Information Science (GIS), we are able to search for a correlation between lower class households and amounts of GHG emissions. After processing the data, we are able to show that there is no trend in GHG emissions and the proximity to lower class households. Towards the end of the project, we were able to see an extremely slight trend of lower amounts of GHG emissions near upper class households. The project also provides the statistics, or any autocorrelation, of the data for significance testing to determine whether or not there is a probability of the relationship. The statistics provided will be the R2 value, regression, and correlation.

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