Microbial communities are an important cornerstone of all ecosystems. By studying their interactions and the way they respond to environmental changes we can better understand which factors contribute to the ability of the community to function. Previous experiments were conducted to gather data on how microbial community composition changes over time of a nutrient perturbation. After collecting this data, the microbial community composition was determined by sequencing of the 16SsrDNA gene. Being able to analyze these datasets of community composition, is where we are able to gain the most understanding of the significance of the community. There are main ways to look at these communities but the main three are the statistical approach, network analysis, and linear systems modeling. Each of these provides a different lens to look at datasets which can be used to give context to the various trends in the
data. Being able to understand how to use each of these methods and determine which is the most useful for any given dataset is an important part of this research.
A student project for AHSE1500: Foundations of Business and Entrepreneurship (taught in Spring 2006) featuring an Olin College themed tradable card game. It consists of cards of students, professors, locations, and events.
This record contains the Final Report for the project and scanned images of all the cards in the game.
The Rockwell Automation SCOPE team worked to provide an out-of-box quality control sensor for automation applications. Quality control sensors need to provide fast inspection capabilities for factories to ensure continuous quality of products. The team also looked into business opportunities for the sensor in line with Rockwell Automation’s industrial customer base. The team optimized the current sensor and made improvements. They also explored market segments where the sensor could make a significant impact on a factory’s quality control and automation processes.