The Use of Scilab-Cloud for Teaching Digital Signal Processing Concepts in Electrical Engineering Curricula
Keywords:
Digital Signal Processing, Scilab Cloud, Engineering EducationAbstract
The digital signal processing (DSP) is a relevant area in the electrical/computer engineering field, since several applications have been observed during the past decades. On the other hand, students have demonstrated difficulties to understand not only the eventual applications, but also its mathematical concepts and theory. Actually, open source packages are available and increasing, but the use of these tools are not very widespread in electrical engineering curriculum. This paper presents the use of Scilab-Cloud software platform for teaching some fundamentals of digital signal processing in undergraduate level, particularly for electrical engineering curriculum. Therefore, some experiments have carried out with undergraduate electrical engineering students and a questionnaire answered by them evidenced the potential of Scilab-Cloud as an interesting alternative tool to foster and motivate students for learning DSP skills.
References
. Baicher. G.S, Sherrington. J.A, Learning about digital signal processing using spreadsheets and simulation software, Engineering Science and Education Journal, pp. 41-48, 1996.
. Zoltowski MD, Allebach JP, Bouman CA. Digital signal processing with applications: a new and successful approach to undergraduate DSP education. IEEE Trans Educ.,39:120‐126, 1996.
. Toral. S.L, Barrero. F and Torres. M.R.M, Analysis of utility and use of a web-based tool for digital signal processing teaching by means of a technological acceptance model, Computes & Education, pp. 957-975, 2005.
. Toral. S.L, Barrero. F, Torres. M.R.M and Gallardo. S, Interactive multimedia teaching of digital signal processors, Computer Applications in Engineering Education, pp. 88-98, 2007.
. B. Balamuralithara, and P.C. Woods, Virtual laboratories in engineering education: the simulation lab and remote lab, Computer Applications in Engineering Education, pp. 108-118, 2008.
. Marozas V, Dumbrava V. Motivating the students to study the basics of digital signal processing by using virtual learning environment. Elektronika ir Elektrotechnika. 102:pp. 87‐90, 2010.
. Algudah Y.A, Al-Qaralleh, E. Project based learning to enhance teaching digital signal processing. International Conference on Interactive Mobile and Computer Aided Learning (IMCL).pp.32.35, 2012.
. So. S, A research-oriented project that motivates undergraduate students in digital signal processing, Proceedings of the 2013 AAEE Conference, Gold Coast, Australia, pp. 2-11, 2013.
. B. L. Sturm, J. D. Gibson, Signals and systems using Matlab: An integrated suite of applications for exploring and teaching media signal processing, in Proc. Annu. Conf. FIE, pp. F2E-21–F2E-26, 2005.
. Kulmer. F, Wurzer. C.G, Geiger. B.C, The magnitude response learning tool for DSP education: a case study, IEEE Transactions on Education, pp. 282-289, 2016.
. Cobos. M, and Roger. S, SART3D: A Matlab toolbox for spatial audio and signal processing education, Computer Applications in Engineering Education, pp. 1-15, 2019.
. Vieira. E.B, Busch. W.F, Prata, D.M and Santos. L.S, Application of Scilab/Xcos for process control applied to chemical engineering educational projects, Computer Applications in Engineering Education, pp. 1-12, 2018.
. Botana, F., Abanades, M.A., Escribano, J. Using a free open source software to teach mathematics, Computer Applications in Engineering Education, pp. 1-8, 2012.
. R. Belu, and I.N.C.Husanu, Using a virtual platform for teaching electrical machines and power systems courses, ASEE Annual Conference and Exposition, pp.1-18, 2013.
. Vatansever. F and Yalcin. N.A, e-Signals & systems: a web-based educational tool for signals and systems, Computer Applications in Engineering Education, pp. 1-17, 2017
. Gonzales. A, Turning a traditional teaching setting into a feedback-rich environment, International Journal of Educational Technology in Higher Education, pp. 1-21, 2018.
. Britain, S., Liber, O. A framework for pedagogical evaluation of virtual learning environments, Educational Cybernetics: Reports. Paper 2, https://hal.archives-ouvertes.fr/hal-00696234/document. 2004, Accessed 30 Sep, 2019.
. Salinas, I., Gimenez, M.H., Gotor, V.P.C, Ortiz, R.S, Monsoriu, J.A. Design and evaluation of a three-dimensional virtual laboratory on vector operations, Computer Applications in Engineering Education, pp. 1-8, 2019.
. Kurelovic, E.K., Rako, S., Tomljanovic, J. Cloud computing in education and student´s needs, 36th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 856-861, 2013.
. Encalada, L.W., Sequera, J.L.C. Collaboration in the cloud for online learning environments: an experience applied to laboratories. Creative Education, pp. 1435-1445, 2015.
. King, T. S. Reviews of cloud computing for education: services and benefits. International Journal of Social Sciences, pp. 1299-1305, 2015.
. Magyar, Z., Záková, K. Using Scilab for building of virtual lab. 9th International Conference on Information Technology Based Higher Education and Training (ITHET), pp. 280- 283, 2010.
. Encalada, L.W., Sequera, J.L.C. Model to implement virtual computing labs via cloud computing services. Symmetry, pp. 1-15, 2017.
. Boukil, N., Ibriz, A. Architecture of remote virtual labs as a service in cloud computing, International Conference on Cloud Technologies and Applications, pp. 1-6, 2015.
. Choudhary, S., Raj, V., Sanmugasundaram, K., Patel, G.S., Moudgalya, K. Scilab on cloud and textbook companion project: a web 2.0 service for open source education, International Conference on Cloud Computing and Big Data, pp. 438-443, 2013.
. Martinez, J.A.G., Lorenzo, M.L.B., Sánchez, E.G. Cloud computing and education: a state-of-the-art survey, Computers & Education, Elsevier, pp. 132-151, 2015.
. Baldassarre, M.T., Caivano, D., Dimauro, G., Gentile, E., Visaggio, G. Cloud computing for education: a systematic mapping study, IEEE Transactions on Education, v. 61, pp. 234-244, 2018.
. Qasem, Y.A.M., Abdullah, R., Jusoh, Y.Y., Atan, R., Asadi, S. Cloud computing adoption in higher education institutions: a systematic review, IEEE Access, v.7, pp. 63722-63744, 2019.
. Mousa-Al, A. Cloud computing: bridging the link between industry and the classroom, International Journal of Electrical Engineering & Education, pp. 1-21, 2019.
. Lathi. B.P, Linear systems and signals, Second Edition, Oxford University Press, Second Edition, 2004.
. Hayes, M. H, Schaum's outline of theory and problems of digital signal processing, McGraw-Hill, 1999.
. Smith, S.W, The Scientist and Engineer’s Guide to Digital Signal Processing, California Technical, 1999.
. Ma S, Liu W, Cai W, Shang Z, Liu G. Lightweight deep residual CNN for fault diagnosis of rotating machinery based on dephwise separable convolutions, IEEE Acess, pp. 57023-57036, 2019.
. Luo, J., Ying, K., Bai, J. Savitzky-Golay smoothing and differentiation filter for even number data, Signal Processing, Elsevier, pp. 1429-1434, 2005.
Downloads
Published
How to Cite
Issue
Section
License
Authors who submit papers with this journal agree to the following terms.