Open Access
Issue
ITM Web Conf.
Volume 35, 2020
International Forum “IT-Technologies for Engineering Education: New Trends and Implementing Experience” (ITEE-2019)
Article Number 01018
Number of page(s) 12
Section Engineering Education Technology Based on Using Digital Resources
DOI https://doi.org/10.1051/itmconf/20203501018
Published online 09 December 2020
  1. H. Haken & J. Portugali, Information and Self-Organization, Entropy, 19(1), p. 18 (2017). doi:10.3390/e19010018 [CrossRef] [Google Scholar]
  2. F. Capra, The systems view of life a unifying conception of mind, matter, and life, Cosmos and History, Vol. 11, I. 2, pp. 242-249 (2015) [Google Scholar]
  3. G. Malinetskii, S. Manenkov, N. Mitin & V. Shishov, A cognitive challenge and information technologies, Herald of the Russian Academy of Sciences, 81(4) (2011). DOI: 10.1134/S1019331611040034. [CrossRef] [Google Scholar]
  4. V.E. Karpov, V.B. Tarassov, Synergetic Artificial Intelligence and Social Robotics, Abraham A., Kovalev S., Tarassov V., Snasel V., Vasileva M., Sukhanov A. (eds) Proceedings of the Second International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’17), IITI 2017, Intelligent Systems and Computing, Vol. 679, Springer, Cham (2018) [Google Scholar]
  5. E.G. Kamensky, Context of NBIC-technologies development: Institutions, ideology and social myths, Mediterranean Journal of Social Sciences, Vol. 6, No. 6, pp. 181-185 (2015) [Google Scholar]
  6. Converging technologies for improving human performance: Nanotechnology, biotechnology, information technology and cognitive science, Ed. by M.C. Roco and W.S. Bainbridge, The Netherlands: Kluwer Academic Publishers (2003) [Google Scholar]
  7. H. Haken, Information and Self-Organization: A Macroscopic Approach to Complex Systems, Springer-Verlag Berlin Heidelberg, p. 258 (2006). DOI: 10.1007/3-54033023-2 [Google Scholar]
  8. D. Novikov, Cybernetics: from Past to Future, Berlin, Springer, p. 107 (2016) [Google Scholar]
  9. A.A. Aleksandrov, P.A. Kapyrin, N.A. Meshkov, K.A. Neusypin, A.E. Popovich & A.V. Proletarsky, Gamification in the advanced higher professional education: Fundamentals of theory and experience of use, International Journal of Civil Engineering and Technology, Vol. 9, I. 11, November 2018, pp. 1800-1808 (2018). Article ID: IJCIET_09_11_176 [Google Scholar]
  10. A.V. Proletarsky and K.A. Neusypin, Particularities of using the modern information technologies in education, European Social Science Journal, Vol. 1-1, pp. 63-65 (2014) [Google Scholar]
  11. V.N. Zimin, S.A. Mardanov and D.A. Sergeev, Theoretical and practical bases of shaping the professional paths for students of IT specialties, International Journal of Experimental Education, Vol. 8, pp. 34-38 (2017) [Google Scholar]
  12. L.D. Feisel & A.J. Rosa, The Role of Laboratory in Engineering Education, Journal Engineering Education, Vol. 94, No. 1, pp. 121-130 (2005) [CrossRef] [Google Scholar]
  13. R.W. Lucky, The future of engineering, IEEE Spectrum, Vol. 35, p. 86 (2002) [CrossRef] [Google Scholar]
  14. T.I. Buldakova & A.Sh. Dzhalolov, Analysis of data processes and choices of dataprocessing and security technologies in situation centers, Scientific and Technical Information Processing 39(2), pp. 127–132 (2012). DOI: 10.3103/S0147688212020116 [CrossRef] [Google Scholar]
  15. R. Paradiso, G. Loriga & N. Taccini, A wearable health care system based on knitted integrated sensors, IEEE Transactions on Information Technology in Biomedicine, Vol. 9, No. 3, pp. 337-344 (2005) [CrossRef] [Google Scholar]
  16. J. Winters & Y. Wang, Wearable sensors and telerehabilitation, IEEE Engineering in Medicine and Biology Magazine, Vol. 22, No. 3, pp. 56-65 (2003) [CrossRef] [Google Scholar]
  17. A. Biswas & P. Sarthak, Smart Collar Short range signal triangulation for animal monitoring, International Journal of Advanced Research, Vol. 4, No. 1, pp. 1528-1535 (2016) [CrossRef] [Google Scholar]
  18. T.Yu. Tsibizova and V.N. Zimin, Development of a way for fulfilling the function of habilitation of students and graduates of educational organizations in the present-day conditions, Automation, Modern Technologies, Vol. 71(10), pp. 465-468 (2017) [Google Scholar]
  19. V.N. Zimin, S.A. Mardanov and D.A. Sergeev, Theoretical and practical bases of shaping the professional paths for students of IT specialties, International Journal of Experimental Education, Vol. 8, pp. 34-38 (2017) [Google Scholar]
  20. T. Buldakova, D. Krivosheeva, Data Protection During Remote Monitoring of Person’s State, Dolinina O at al (eds) Recent Research in Control Engineering and Decision Making, ICIT-2019. Studies in Systems, Decision and Control, Vol. 199, Springer, Cham, pp. 3-14 (2019). https://doi.org/10.1007/978-3-030-12072-6_1. [Google Scholar]
  21. T.I. Buldakova, Cybersecurity Risks Analyses at Remote Monitoring of Object’s State, Kravets A., Bolshakov A., Shcherbakov M. (eds) Cyber-Physical Systems: Industry 4.0 Challenges, Studies in Systems, Decision and Control, Vol. 260, Springer, Cham (2020). DOI: 10.1007/978-3-030-32648-7_15. [Google Scholar]
  22. S.I. Suyatinov, Conceptual Approach to Building a Digital Twin of the Production System, Kravets A., Bolshakov A., Shcherbakov M. (eds) Cyber-Physical Systems: Industry 4.0 Challenges, Studies in Systems, Decision and Control, Vol. 259, Springer, Cham (2020). DOI: 10.1007/978-3-030-32579-4_22. [Google Scholar]
  23. J. Herwan, S. Kano, O. Ryabov, H. Sawada & N. Kasashima, Cyber-physical system architecture for machining production line, 2018 IEEE Industrial Cyber-Physical Systems (ICPS), pp 387-391 (2018). https://doi.org/10.1109/ICPHYS.2018.8387689. [CrossRef] [Google Scholar]
  24. O. Sénéchal & D. Trentesaux, A framework to help decision makers to be environmentally aware during the maintenance of cyber physical systems, Environmental Impact Assessment Review, 77, pp. 11-22 (2019). http://dx.doi.org/10.1016/j.eiar.2019.02.007. [CrossRef] [Google Scholar]
  25. S. Chernyshev, Cyber-Physical Principles of Information Processing in UltraWideband Systems, Kravets A., Bolshakov A., Shcherbakov M. (eds), Cyber-Physical Systems: Industry 4.0 Challenges. Studies in Systems, Decision and Control, Vol. 260, Springer, Cham (2020). DOI: 10.1007/978-3-030-32648-7_1. [Google Scholar]
  26. S.I. Suyatinov, Criteria and Method for Assessing the Functional State of a Human Operator in a Complex Organizational and Technical System, Global Smart Industry Conference (GloSIC), Chelyabinsk, Russia, pp. 1-6 (2018). http://dx.doi.org/10.1109/GloSIC.2018.8570088. [Google Scholar]
  27. M. Kedadouche, M. Thomas, A. Tahan & R. Guilbault, Nonlinear Parameters for Monitoring Gear: Comparison Between Lempel-Ziv, Approximate Entropy, and Sample Entropy, Complexity Shock and Vibration, article ID 959380, pp. 1-12 (2015). http://dx.doi.org/10.1155/2015/959380 [Google Scholar]
  28. F. Isik, An Entropy-Based Approach for Measuring Complexity in Supply Chains, International Journal of Production Research 48(12), pp. 3681-3696 (2010) [CrossRef] [Google Scholar]
  29. T.I. Buldakova and S.I. Suyatinov, Assessment of the State of Production System Components for Digital Twins Technology, Kravets A., Bolshakov A., Shcherbakov M. (eds) Cyber-Physical Systems: Industry 4.0 Challenges, Systems, Decision and Control, Vol. 259 (2020). Springer, Cham. DOI: 10.1007/978-3-030-32579-4_20 [Google Scholar]
  30. S.M. Pincus, Approximate entropy (ApEn) as complexity measure, Chaos, Vol. 5, No. 1, pp. 110–117 (1995) [CrossRef] [Google Scholar]

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