Virtual Conference
July 26, 2021
July 26, 2021
July 19, 2022
Computing and Information Technology Division Poster Session
Computing and Information Technology
11
10.18260/1-2--37461
https://peer.asee.org/37461
462
Soren Henrichsen is a student at Utah Valley University. His interests include artificial intelligence, algorithms, robotics, machine learning, and statistics.
Reza Sanati-Mehrizy is a professor of the Computer Science Department at Utah Valley University, Orem, Utah. He received his M.S. and Ph.D. in Computer Science from the University of Oklahoma, Norman, Oklahoma. His research focuses on diverse areas such as Database Design, Data Structures, Artificial Intelligence, Robotics, Computer-Aided Manufacturing, Data Mining, Data Warehousing, and Machine Learning.
Afsaneh Minaie is a Professor and Chair of Engineering Department at Utah Valley University. She received her B.S., M.S., and Ph.D. all in Electrical Engineering from University of Oklahoma. Her research interests include gender issues in the academic sciences and engineering fields, Embedded Systems Design, Mobile Computing, Wireless Sensor Networks, Nanotechnology, Data Mining and Databases.
This paper outlines the linear transform sort and its ideal and worst use cases. In general, a transform sort generates new keys in the range from 0 to n by a mathematical transformation, then uses those keys to sort the data set. We will prove the functionality of the linear transform sort and show that the complexity is O(n) for flat data distributions, and O(n^2) in the worst case. Linear transform sorting may be useful for flat data distributions but is mostly a proof of concept for future transform sorting algorithms, such as adaptive transformations or specific transformations for normally distributed data or other known data distributions
Henrichsen, S. P., & Sanati-Mehrizy, R., & Minaie, A. (2021, July), Linear Transform Sort Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37461
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