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Extraction of information and facts from data mining of random sequences for undergraduate research

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Collection

2017 Mid-Atlantic Section Fall Conference

Location

Penn State University - Berks Campus - Reading, Pennsylvania

Publication Date

October 6, 2017

Start Date

October 6, 2017

End Date

October 7, 2017

Conference Session

Mid Atlantic Papers

Tagged Topic

Mid-Atlantic Section Fall Conference

Page Count

7

Permanent URL

https://peer.asee.org/29377

Download Count

37

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Paper Authors

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sunil Dehipawala Queensborough Community College

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Sunil Dehipawala received his B.S. degree from University of Peradeniya in Sri Lanka and Ph.D from City University of New York. Currently, he is working as a faculty member at Queensborough Community College of CUNY.

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Raul Armendariz Queensborough Community College

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Assistant professor of physics

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George Tremberger Jr CUNY Queensborough Community College

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Tak Cheung CUNY Queensborough COmmunity College

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Tak Cheung, Ph.D., professor of physics, teaches in CUNY Queensborough Community College. He also conducts research and mentors student research projects.

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Abstract

A general method to extract information and facts from data mining of random sequences in biology and astronomy has been developed. The random sequence analysis has been implemented in several NSF-REU projects using NIH and NASA databases. Examples of RNA sequence with reference to Shannon-entropy based bioinformatics and SDO magnetic topology analysis with reference to solar physics are presented. The contrast to Brookhaven Synchrotron and high energy physics data analysis is also discussed. The feedback of administrating REU projects to our physics teaching for engineering students was found to be valuable and the examples of magnetic reconnection and geomagnetic induced current are presented. Therefore community college REU project provides connectedness awareness in the linking of previous published reports, critical thinking in result interpretation, and career development when going onto a senior college REU program, the top three benefits of college education, according to a 2016 July Money Magazine ”Value of College” survey.

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