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Haptics in Aviation

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Computing and Information Technology Division Technical Session 7

Tagged Division

Computing and Information Technology

Tagged Topic

Diversity

Page Count

12

Permanent URL

https://peer.asee.org/37239

Download Count

180

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Paper Authors

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Afsaneh Minaie Utah Valley University

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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.

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Joshua D. Neeley Utah Valley University

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Joshua Neeley is an Electronics Engineer working for the United States Air Force. He received his B.S. in Computer Engineering from Utah Valley University. He is currently expecting to begin and pursue a M.S. in Computing from the University of Utah starting in the Fall for 2021. His academic interests include, Haptics, Robotics, and Computer Science.

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Nile Edward Brewer

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Nile Brewer works as a Controls Specialist and High Voltage Electrician. He received his B.S. in Computer Engineering at Utah Valley University. His research interests are Design and Safety Practices for Power Distribution, Aviation, Embedded Systems Design, Control Systems, Open-Source Applications.

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Reza Sanati-Mehrizy Utah Valley University

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Reza Sanati-Mehrizy is a professor of 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.

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Abstract

Abstract According to Wikipedia “machine learning is the study of computer algorithms that improve automatically through experience. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so”. Machine learning has many applications such as banking, bioinformatics, adaptive websites, computer networks, economics, linguistics, online advertising, self-driving cars, dynamic pricing, traffic alerts, social media, search engines, speech recognition, online video streaming, IOT, … Machine learning has become a revolutionary modern engineering tool to solve real-world engineering problems. Because of availability of computing power, more and more engineering problems have been reformulated and solved using this data-driven approach. It is essential for engineers to know how to apply machine learning algorithms to their large amount of data that is generated by the sensors. Educational excellence requires exposing students to the current edge of research. To ensure that student projects are along the same trajectory that the industry is moving, educators must continually introduce emerging techniques, practices, and applications into the curriculum. The field of machine learning is growing rapidly. It is essential that the emerging field of machine learning be integrated into the computer science and engineering curricula. This paper is a study of different approaches that are used by different institutions of higher education around the world to integrate machine learning concepts in their computer science and engineering curricula.

Minaie, A., & Neeley, J. D., & Brewer, N. E., & Sanati-Mehrizy, R. (2021, July), Haptics in Aviation Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37239

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