The Nature of the Computing and Natural Science in Engineering Education-Reference-Cited by-同舟云学术

The Nature of the Computing and Natural Science in Engineering Education

Published:2021-07-05 Issue: Volume: Page:69-76
ISSN:2789-181X
Container-title:Journal of Computing and Natural Science
language:en
Short-container-title:JCNS

Author:

Andonova Bojadzievski¹,kulkarni Ramesh¹

Affiliation:

1. School of Computer Science and Information Technology, University American College North Macedonia

Abstract

In engineering, the interdisciplinary essence of the Computing and Natural Science (CNS) as well as its relations with other fields are described. This paper presents a discussion of the phases by which CNS education evolve from the recognition of initial growth in the '80's to current growth. The limitations and potential benefits of varying CNS education methodologies are addressed, and so is the advancement of the number of the foundational elements, which are common to most strategies. The CNS course content, grades and curriculum are examined and all bachelors’ programs are surveyed. The curricula of the various programs are examined and discussed for their relative weighting for the standard "toolkit."

Publisher

Anapub Publications

Link

http://anapub.co.ke/journals/jcns/jcns_pdf/2021/jcns_volume_1-issue_3/JCNS202101011.pdf

Reference12 articles.

1. W. Yang, K. Li and K. Li, "A hybrid computing method of SpMV on CPU–GPU heterogeneous computing systems", Journal of Parallel and Distributed Computing, vol. 104, pp. 49-60, 2017. Available: 10.1016/j.jpdc.2016.12.023.

2. S. Pllana and J. Barhen, "Introduction to the computing special issue: performance portability and tuning for multi-core and many-core computing systems", Computing, vol. 96, no. 12, pp. 1113-1114, 2013. Available: 10.1007/s00607-013-0379-0.

3. Z. Zhou, C. Tang, Y. Liu, Y. Liu and J. Xu, "Visual Analytics for Multidimensional Time-Varying Data via Dimension Reduced Visual Perception", Journal of Computer-Aided Design & Computer Graphics, vol. 30, no. 7, p. 1194, 2018. Available: 10.3724/sp.j.1089.2018.16713.

4. A. Haldorai and A. Ramu, “Security and channel noise management in cognitive radio networks,” Computers & Electrical Engineering, vol. 87, p. 106784, Oct. 2020. doi:10.1016/j.compeleceng.2020.106784

5. A. Haldorai and A. Ramu, “Canonical Correlation Analysis Based Hyper Basis Feedforward Neural Network Classification for Urban Sustainability,” Neural Processing Letters, Aug. 2020. doi:10.1007/s11063-020-10327-3

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