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Turbidity measurements provide the primary source of performance monitoring at many water treatment plants. Turbidity provides an excellent way to measure overall plant performance, but it does not provide insight as to why the water treatment plants are performing well or poorly. The Floc Size and Count App team aims to overcome this problem by creating a tool for operators to analyze flocculation as a means to understand plant efficiency and performance as well as to understand the underlying reasons for this.
Spring 2017
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Members Deniz Yilmazer: dy223@cornell.edu Melanie Lim: ml876@cornell.edu Shaima Parveen: sp822@cornell.edu
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This semester, the team has primarily worked on improving the data outputted by the Floc App. Distances in a computer are originally stored in units of pixels (tiny squares that are combined together to form store and display digital images). This unit must be converted to micrometers (a physical unit of length) using some scaling constant. The Floc App originally had this factor fixed, which would provide inaccurate measurements for different lab setups. To deal with this, the team created a function that allows a user to set this factor.
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The team started the implementation of an easy-to-use desktop application that would measure floc size distribution that is written in LabVIEW. The team completed image acquisition and analysis parts for the final application. The connection of these two separate programs were not finished this semester. The team also increased readability of the existing code by the partitioning the code into subsections via the creation of functions.\
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Members
Deniz Yilmazer: dy223@cornell.edu
Anthony Verghese: akv26@cornell.edu
Christian Rodriguez: cer95@cornell.edu
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Documents
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