CFP last date
22 April 2024
Reseach Article

Engineering Education: Computer-Aided Engineering with MATLAB; Discrete Wavelet Transform as a Case Study

by Abdul Rasak Zubair, Yusuf Kola Ahmed
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 46
Year of Publication: 2019
Authors: Abdul Rasak Zubair, Yusuf Kola Ahmed
10.5120/ijca2019918598

Abdul Rasak Zubair, Yusuf Kola Ahmed . Engineering Education: Computer-Aided Engineering with MATLAB; Discrete Wavelet Transform as a Case Study. International Journal of Computer Applications. 182, 46 ( Mar 2019), 6-17. DOI=10.5120/ijca2019918598

@article{ 10.5120/ijca2019918598,
author = { Abdul Rasak Zubair, Yusuf Kola Ahmed },
title = { Engineering Education: Computer-Aided Engineering with MATLAB; Discrete Wavelet Transform as a Case Study },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2019 },
volume = { 182 },
number = { 46 },
month = { Mar },
year = { 2019 },
issn = { 0975-8887 },
pages = { 6-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number46/30459-2019918598/ },
doi = { 10.5120/ijca2019918598 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:14:24.058139+05:30
%A Abdul Rasak Zubair
%A Yusuf Kola Ahmed
%T Engineering Education: Computer-Aided Engineering with MATLAB; Discrete Wavelet Transform as a Case Study
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 46
%P 6-17
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Engineering education is to move engineering students along the progressive path from being novices toward becoming experts in design, problem-solving and application of knowledge. Engineering problem may require more computations than is possible by hand. Computer-aided engineering is the process of solving engineering problems with the aid of computer software. Engineering Lecturers need to help engineering students to develop expertise in Computer-aided engineering with examples. The development of Discrete Wavelet Transformation is used as a case study. A wavelet is a small wave whose energy is concentrated in time. Wavelets applications include signal processing, noise filtering, image processing, and document analysis. Among wavelet families, Haar wavelet is selected. Scientific representations of the problem and a logical plan of attacking the problem are presented. Necessary equations are derived. A modular approach to programming is demonstrated. A complex problem is broken down into simple tasks and steps which are coded into simple short MATLAB programs. A program calls another program to execute some specific tasks. Programs are checked against possible errors using a situation where the answers are known. Discrete wavelet transformation and inverse discrete wavelet transformation for 1D, 2D, and 3D discrete-time signals have been implemented. 2D gray level images and 3D color images are also considered. The use of similar examples is recommended for Engineering Lecturers.

References
  1. National Research Council, 2012. “Discipline-Based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering” Singer, S. R., Nielsen, N. R. and H. A. Schweingruber, H. A.Editors. Committee on the Status, Contributions, and Future Directions of Discipline-Based Education Research. Board on Science Education, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.
  2. Docktor, J. L., and Mestre, J. P. 2011. “A synthesis of discipline-based education research in physics”, Paper presented at the Second Committee Meeting on the Status, Contributions, and Future Directions of Discipline-Based Education Research. Available: http://www7.nationalacademies.org/bose/DBER_Docktor_October_Paper.pdf.
  3. Svinicki, M. 2011. “Synthesis of the research on teaching and learning in engineering since the implementation of ABET engineering criteria 2000”, Paper presented at the Second Committee Meeting on the Status, Contributions, and Future Directions of Discipline-Based Education Research. Available: http://www7.nationalacademies.org/bose/DBER_Svinicki_October_Paper.pdf.
  4. Bassok, M. and Novick, L. R. 2012. “Problem solving”, In Holyoak, K. J. and Morrison, R. G. (Eds.), Oxford handbook of thinking and reasoning, 413-432. New York: Oxford University Press.
  5. Martinez, M. E. 2010. Learning and cognition: The design of the mind. Upper Saddle River, NJ: Merrill.
  6. Hsu, L., Brewe, E., Foster, T. M., and Harper, K. A. 2004. “Resource letter RPS-1: Research in problem solving”, American Journal of Physics, 72(9), 1147-1156.
  7. Whitson, L., Bretz, S. L., and Towns, M. H. 2008. “Characterizing the level of inquiry in the undergraduate laboratory”. Journal of College Science Teaching, 37(7), 52-58.
  8. Ericsson, K. A., Krampe, R. Th., and Tesch-Römer, C. 1993. “The role of deliberate practice in the acquisition of expert performance”. Psychological Review, 100(3), 363-406.
  9. Yildirim, T., Shuman, L., and Besterfield-Sacre, M. 2010. “Model-eliciting activities: Assessing engineering student problem solving and skill integration processes”, International Journal of Engineering Education, 26(4), 831-845.
  10. Zubair A. R. 2009. “Numerical Integration Based Analysis of Pulse Width Modulated Voltage Source Inverter”, In A. Gyasi-Agyei and T. Ogunfunmi (Eds.). Adaptive Science and Technology: Proceedings of the 2nd IEEE International Conference on Adaptive Science and Technology (ICAST). 14-16 December, 2009. Accra, 301–307. Available at https://ieeexplore.ieee.org/document/5409707.
  11. Zubair A. R. and Olatunbosun A. 2014. “Arithmetic and Logical Models of Transmission Line Stranded Conductors for Voltage and Voltage-Drop Analysis”, International Journal of Innovation and Scientific Research, 8(2), 200-209.
  12. Zubair A. R. and Olatunbosun A. 2014. “Computer Aided Root-Locus Numerical Technique”, Nigerian Journal of Technology, 33(1), 1-13.
  13. Hahn B. and Valentine D. T. 2007. Essential MATLAB for Engineers and Scientists. Burlington: Elsevier.
  14. MathWorks (Matlab). 2018. ‘‘Documentation for MathWorks products’’ Available: https://ch.mathworks.com/help/index.html.
  15. Soman, K. P. 2010. Insight into wavelets: From theory to practice. PHI Learning Pvt. Ltd, 45-237.
  16. Mallat, S. 2008. A wavelet tour of signal processing: the sparse way. Academic press, 80-336.
  17. Burrus, C. S., Gopinath, R. A., Guo, H., Odegard, J. E. and Selesnick, I. W. 1998. Introduction to wavelets and wavelet transforms: a primer. New Jersey, Prentice hall, 1, 7-111.
  18. Donoho, D. L. and Johnstone, I. M. 1994. “Ideal denoising in an orthonormal basis chosen from a library of bases”. Comptes Rendus de l’Académie Des Sciences. Série I, Mathématique, 319(12), 1317–1322.
  19. Van Fleet, P. J. 2011. Discrete wavelet transformations: An elementary approach with applications. John Wiley & Sons, 157-346.
  20. Hongqiao L. and Shengqian W. 2009. "A New Image Denoising Method Using Wavelet Transform", International Forum on Information Technology and Applications (IFITA), Chengdu, 111-114.
  21. Mithun, V. K., Pandey, P., Sebastian, P. C., Mishra, T. P. 2011. “A wavelet based technique for suppression of EMG noise and motion artifact in ambulatory ECG”, Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, 7087–7090.
  22. Zubair A. R., Ahmed Y. K. and Akande K. A. 2018. “Electromyography Noise Suppression in Electrocardiogram Signal Using Modified Garrote Threshold Shrinkage Function”, African Journal of Computing & ICT, 11(3), 85-94.
Index Terms

Computer Science
Information Sciences

Keywords

Engineering Education Problem-solving Computer-aided engineering MATLAB Discrete Wavelet transformation.