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IJSTR >> Volume 10 - Issue 2, February 2021 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Switching Matrix Architecture For Flexible Remote Experiments Of Circuits Structuring In Electronics And Electricity While Using An Intelligent Algorithm

[Full Text]

 

AUTHOR(S)

Yassine Larbaoui, Ahmed Naddami, Ahmed Fahli

 

KEYWORDS

Circuits structuring, e-learning, electronic board, flexible remote experiments, intelligent algorithm, matrix architecture, remote control, remote lab.

 

ABSTRACT

This paper presents the development of a switching matrix architecture within VISIR system for flexible remote experiments in electronics and electricity while relying on an intelligent algorithm at the software level for experiments control and monitoring through internet. The switching matrix is relying on a developed electronic board topology to enable the interconnection between any two components on VISIR system for remote circuits structuring. The developed intelligent algorithm at the software level enables to have a dynamic control and monitoring on circuits building within VISIR system while respecting the electrical limits of using the current and voltage, where the remote control and monitoring on electrical and electronic components within the switching matrix architecture. The developed switching matrix architecture and the developed algorithm enable to have flexible remote experiments and resilient control on circuits structuring for e-learning purposes, in addition of having more circuit combinations of experiments by offering the possibility of connecting any component to any other component on VISIR system.

 

REFERENCES

[1] G. Attwell. Evaluating E-learning: A Guide to the Evaluation of E-learning. vol. 2, Evaluate Europe Handbook Series. 2006.
[2] Bahar, Soegiarto. Development Of Instructional Media Based On Mobile Technology To Enriching Teaching Material For Primary School Students In Indonesia Post-Learning In The Classrooms. International Journal of Scientific and Technology Research, vol. 9, no. 1, pp. 94–98. 2020.
[3] J. K. Lee, W. K. Lee. The relationship of e-learner’s self-regulatory efficacy and perception of e-learning environmental quality. J. Computers in Human Behavior, vol. 24, no. 1, pp. 32–47. 2008.
[4] F. Rohman, A. Fauzan, Yohandri. Project, Technology And Active (PROTECTIVE) Learning Model To Develop Digital Literacy Skills In The 21st Century. International Journal of Scientific and Technology Research, vol. 9, no. 1, pp. 12–16. 2020.
[5] A. G. abdel WAHAB. Modeling students’ intention to adopt e-learning: A case from Egypt, The Electronic Journal of Information Systems in Developing Countries. Computers in Human Behavior, vol. 34, no. 1, pp. 1-13. 2008.
[6] B. C. Lee, J. O. Yoon, I. Lee. Learners acceptance of e-learning in south korea: Theories and results. Computers & Education, vol. 53, no. 4, pp. 1320–1329. 2009.
[7] M. Aparicio, F. Bacao, T. Oliveira. Learners acceptance of e-learning in south korea: Theories and results. J. Computers in Human Behavior, vol. 6, no. 6, pp. 388–399. 2017.
[8] S. Eom, N. J. Ashill. A system’s view of e-learning success model. Decision Sciences Journal of Innovative Education, vol. 16, no. 1, pp. 42–76. 2018.
[9] H. M. Selim. Critical success factors for e-learning acceptance: Conrmatory factor models. J. Computers and Education, vol. 49, no. 2, pp. 396–413. 2007.
[10] S. Ozkan, R. Koseler. Multi-dimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation. J. Computers and Education, vol. 53, no. 4, pp. 1285–1296. 2016.
[11] Y. S. Wang. Assessment of learner satisfaction with asynchronous electronic learning systems. J. Information Management, vol. 4, no. 1, pp. 75–86. 2001.
[12] J. Mtebe, C. Raphael. Key factors in learners’ satisfaction with the e-learning system at the university of dar es salaam, Tanzania. Australasian Journal of Educational Technology, vol. 43, no. 4, pp. 75–86. 2018.
[13] R. Heradio, L. de la Torre Cubillo, D. Galan, F. J. Cabrerizo, E. H. Viedma, S. Dormido. Virtual and remote labs in education: A bibliometric analysis. J. Computers & Education, vol. 98, 14–38. 2016.
[14] R. Heradio, L. de la Torre Cubillo, S. Dormido. Virtual and remote labs in control education: A survey. J. Annual Reviews in Control, vol. 42, pp. 1–10. 2016.
[15] C. Viegas, all. Impact of a remote lab on teaching practices and student learning, J. Computers & Education, vol. 126, pp. 201–216. 2018.
[16] M. Tawfik, and all. Online experiments with dc/dc converte. J. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, vol. 10, no. 4, pp. 310–318. 2015.
[17] R. Najimaldeen, G. Ribeiro, A. Pedro, G. I. Gustavsson. Using uml models to describe the visir system. International Journal of Online Engineering, vol. 12, no. 6, pp. 310–318. 2016.
[18] U. H. Jayo, J. G. Zubia. Remote measurement and instrumentation laboratory for training in real analog electronic experiments. International Journal of Online Engineering, vol. 12, no. 6, pp. 310–318. 2016.
[19] J. G. Zubia, and all. Empirical analysis of the use of the visir remote lab in teaching analog electronics. IEEE Transactions on Education, vol. 60, no. 2, pp. 149–156. 2017.
[20] J. L. Hardison, K. DeLong, P. H. Bailey, V. J. Harward, Deploying interactive remote labs using the iLab shared architecture. In Proc. 38th Annual Frontiers in Education Conference, Saratoga Springs, NY, USA, IEEE. 2008.
[21] J. Chacon, and all. Ejs, jil server, and LabVIEW: An architecture for rapid development of remote labs. J. IEEE Transactions on Learning Technologies, vol. 8, no. 4, pp. 393–401. 2015.
[22] G. C. Oproiu. A study about using e-learning platform (moodle) in university teaching process. J. Procedia - Social and Behavioral Sciences, vol. 180, pp. 426–432. 2015.
[23] S. B. Atiku, A. Aaron, G. K. Job, and all. Survey On The Applications Of Artificial Intelligence In Cyber Security. International Journal of Scientific and Technology Research, vol. 9, no. 10. 2020.
[24] P. Malik, M. Gupta. An Overview Of Iot Operating System: Contiki Os And Its Communication Models. International Journal of Scientific and Technology Research, vol. 9, no. 10. 2020.
[25] V. C. Muller, N. Bostrom. Future Progress in Artificial Intelligence: A Survey of Expert Opinion. In Fundamental Issues of Artificial Intelligence, 1st ed. Vol. 376, Springer, pp. 555–572. 2017.
[26] T. Miller. Explanation in artificial intelligence: Insights from the social sciences. International Journal of Artificial Intelligence, vol. 267, pp. 1–38. 2019.
[27] C. W. Chang, H. W. Lee, C. Liu. A review of artificial intelligence algorithms used for smart machine tools. Journal of Inventions, vol. 3, no. 3. 2018.
[28] M. Naumovic, D. Zivanovic. Remote experiments in control engineering education laboratory. International Journal of Online Engineering, vol. 4, no. 2, pp. 48–53. 2008.
[29] E. Scanlon, C. Colwell, M. Cooper, T. D. Paolo. Remote experiments, re-versioning and re-thinking science learning. J. Computers and Education, vol. 43, no. 1, pp. 153–163. 2004.