Author(s):
Moskvichev Vladimir Viktorovich
Dr. , Professor
Position: Director
Office: Federal Research Center for Information and Computational Technologies,Siberian Federal University
Address: 660049, Russia, Krasnoyarsk, Mira pr., 53
Phone Office: (391) 227-29-12
E-mail: krasn@ict.nsc.ru
SPIN-code: 9332-6468

Nicheporchuk Valeriy Vasilyevich
Dr.
Position: Senior Research Scientist
Office: Institut of Computing Simulation of SB RAS
Address: 660036, Russia, Krasnoyarsk, Akademgorodok, 50/44
Phone Office: (913) 830-5949
E-mail: valera@icm.krasn.ru
SPIN-code: 7018-8279

Postnikova Ulyana Sergeevna
PhD.
Position: Senior Fellow
Office: Reshetnev Siberian State University of Science and Technology,Federal Research Center for Information and Computational Technologies
Address: 660037, Russia, Krasnoyarsk, Office L-409, 410, 31, Krasnoyarsky Rabochy Av.
Phone Office: (923)-281-94-64
E-mail: ulyana-ivanova@inbox.ru
SPIN-code: 5790-6393

Taseiko Olga Viktorovna
PhD. , Associate Professor
Position: Head of Chair
Office: Federal Research Center for Information and Computational Technologies, Reshetnev Siberian State University of Science and Technology
Address: 660037, Russia, Krasnoyarsk, Office L-409, 410, 31, Krasnoyarsky Rabochy Av.
Phone Office: (923)-280-52-10
E-mail: taseiko@gmail.com
SPIN-code: 4032-4299

References:

[1] Dallat C., Salmon P., Goode N. Identifying risks and emergent risks across sociotechnical systems: the NETworked hazard analysis and risk management system (NET-HARMS). Theoretical Issues in Ergonomics Science. 2018; 19(4):456–482. DOI:10.1080/1463922X.2017.1381197. Available at: https://www.tandfonline.com/doi/abs/10.1080/1463922X.2017.1381197?journalCode=ttie20.

[2] Neirotti P., Marco A., Cagliano A.C., Scorrano F. Current trends in Smart City initiatives: some stylised facts. Cities. 2014; (38):25–36. DOI:10.1016/j.cities.2013.12.010. Available at: https://www.sciencedirect.com/science/article/abs/pii/S0264275113001935.

[3] Scheer D. Risk governance and emerging technologies: learning from case study Integration. Journal of Risk Research. 2013; (3–4):355–368. DOI:10.1080/13669877.2012.729519. Available at: https://www.tandfonline.com/doi/abs/10.1080/13669877.2012.729519.

[4] Knijff P., Allford L., Schmelzer P. Process safety leading indicators — a perspective from Europe. Process Safety Management — Improving Performance. 2013; 32(4):332–336. DOI:10.1002/prs.11641. Available at: https://aiche.onlinelibrary.wiley.com/doi/10.1002/prs.11641.

[5] Leveson N. A systems approach to risk management through leading safety indicators. Reliability Engineering and System Safety. 2015; (136):17–34. DOI:10.1016/j.ress.2014.10.008. Available at: http://sunnyday.mit.edu/leadingindicators-published.pdf.

[6] Oien K., Utne I.B., Tinmannsvik R.K., Massaiu S. Building safety indicators: part 2 —application, practices and results. Safety Science. 2011; 49(2):162–171. Available at: https://trid.trb.org/view/1083888.

[7] Goodfellow I., Bengio Y., Courville A. Deep learning. London: MIT Press; 2016: 653.

[8] Kossiakoff A., Sweet W.N., Seymor S.J., Biemer S.M. System engineering principles and practice. New Jersey: Wiley; 2011: 624.

[9] Malinetskii G.G., Podlazov A.V., Kuznetsov I.V. On a national scientific monitoring system. Herald of the Russian Academy of Sciences. 2005; 75(4):323–336. Available at: https: //www.elibrary.ru/item.asp?id=9133358.

[10] Negus C., Henry W. Docker containers. Build and deploy with Kubernetes, Flannel, Cockpit, and Atomic. London: Pearson Education; 2015: 319.

[11] Mouat A. Using Docker: developing and deploying software with containers. Sebastopol: O’Reilly Media; 2015: 328.

[12] Nozhenkova L.F. Information management systems in the territorial and corporate management. Journal of Computational Technologies. 2013; 18(1):52–59. Available at: https: //www.elibrary.ru/item.asp?id=22575114.

[13] ISO 22300:2021 Security and resilience — vocabulary. Available at: https://www.iso.org/ru/standard/77008.html.

[14] PreventionWeb. The knowlege platform for disaster risk reduction. Available at: www.preventionweb.net/Terminology.

[15] Zaki M.J., Wagner M.J. Data mining and machine learning fundamental concepts and algorithms. Cambridge: Cambridge University Press; 2020: 760.

[16] Penkova T.G., Korobko A.V., Nicheporchuk V.V., Nozhenkova L.F. On-line control of the state of technosphere and environment objects in Krasnoyarsk region based on monitoring data. International Journal of Knowledge-Based and Intelligent Engineering Systems. 2016; 20(2):65–74. DOI:10.3233/KES-160330. Available at: https://www.elibrary.ru/item.asp?id=27075197.

[17] Bychkov I.V., Vladimirov D.Ya., Oparin V.N., Potapov V.P., Shokin Yu.I. Mining information science and Big Data concept for integrated safety monitoring in subsoil management. Journal of Mining Science. 2016; 52(6):1195–1209. DOI:10.1134/S1062739116061747. Available at: https://www.elibrary.ru/item.asp?id=31142560.

[18] Ivanova U.S., Taseiko O.V., Chernykh D.A. Probabilistic methods for risk assessment of anthropogenic accidents and emergency. Procedia Structural Integrity. 2019: 136–142. DOI:10.1016/j.prostr.2019.12.129. Available at: https://www.elibrary.ru/item.asp?id=43253864.

[19] Ivanova U.S., Moskvichev V.V., Taseiko O.V. Classifying of Krasnoyarsk territory using a risk-based approach. Issues of Risk Analysis. 2019; 16(4):48–63. DOI:10.32686/1812-5220-2019-16-4-48-63. Available at: https://www.elibrary.ru/item.asp?id=39239488.

[20] Penkova T., Nicheporchuk V. Metus A. Comprehensive operational control of the natural and anthropogenic territory safety based on analytical indicators. Lecture Notes in Computer Science. 2017; (10313):263–270. DOI:10.1007/978-3-319-60837-2 22. Available at: https://www.elibrary.ru/item.asp?id=31044573.

[21] Geoportal of ICM SB RAS. Available at: https://gis.krasn.ru/blog.

[22] DRMKC-INFORM. Country risk profile. Available at: https://drmkc.jrc.ec.europa.eu/inform-index/INFORM-Risk/Country-Risk-Profile.