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Mathematical and Technical Quantitative Methods for Risk Assessment in Public Crisis Management

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EN
Abstrakty
EN
The article shows that in crisis management, risks can be effectively analysed and managed by rational use of mathematical and technical methods. It presents two quantitative methods for risk assessment and a procedure for transferring the results to logistical social networks (LSNs). The need to use social logistical networks, where modern techniques can be applied, including the Internet of Things (IoT) or Machine-to-Machine (M2M) communication, enabling the collection of any amount of data to logistical social networks, is indicated. The article stresses that research on public crisis management must be interdisciplinary in nature, taking into account all aspects of security management, including social, technical and economic issues. Modern methods of assessing the state and risk of a crisis situation of individual elements of the systems generate an increasing number of data, the collection, collection, processing and sharing of which requires ensuring information security and protecting the personal freedom of the individual.
Twórcy
  • Faculty of Management, Warsaw University of Technology, pl. Politechniki 1, 00-661 Warsaw, Poland
Bibliografia
  • 1. Ahmad F., Marwat SNK, Zaki Y., Mehmood Y. and Görg C.: Machine-to-Machine sensor data multiplexing using LTE-advanced relay node for logistics. In: Kotzab H., Panek J., Thoben K.D. (Eds): Dynamics in Logistics, Proceedings of the 4th International Conference LDIC, Bremen, Germany 2014, 247-258.
  • 2. Atzori L., Iera A. and Morabito G.: SloT: giving a social structure to the internet of things. IEEE Communications Letters, 15(11), Nov. 2011, 1193-1195.
  • 3. Cempel Cz.: Vibroacoustic diagnostics of machines. PWN, Warsaw 1989.
  • 4. Chang Y.-C.: Study of overload control problem for intelligent LTE M2M communication system. Advances in Smart Systems Research, 3(3), 2013, 44–48.
  • 5. Directive 96/82/EC on the control of major-accident hazards involving dangerous substances called Seveso II Directive as amended by Directive 2012/18/EU of the European Parliament and of the Council of 4 July 2012 on the control of majoraccident hazards involving dangerous substances,
  • amending and subsequently repealing Council Directive 96/82/EC, Official Journal of the EU L 197.
  • 6. Haller S., Karnouskos S., Schroth C.: The internet of things in an enterprise context. In: The first Future Internet Symposium (FIS), Vienna, Austria, September 2008, 14-28.
  • 7. INET Framework, Accessed: 21-July-2018, https://inet.omnetpp.org.
  • 8. Kaplan S., Garrick B.J.: On the quantitative definition of risk. Risk Analysis, 1, 1981,11-27.
  • 9. Kaplan S.: The words of risk analysis. Risk Analysis, 17, 1997, 407-417.
  • 10. Kisilowski J., Kisilowski M., Radkowski S.: Technical diagnosis in risk assessment in property insurance. Diagnostyka 2000, II International Congress of Technical Diagnostics, Warsaw, Poland, 19-22 September 2000.
  • 11. Kisilowski J.: An analysis of the parametric sensitivity of the eigenvalues of the linear mathematical model of a mechanical system. Building Machines Archives, 31, 1984, 3-4.
  • 12. Kisilowski J.: Dynamics of the Mechanical System Rail Vehicle-Track. PWN, Warsaw 1992.
  • 13. Kisilowski M.: Principles of insurance risk management for machinery and technical equipment, dissertation, Orgmasz, Warsaw 2002.
  • 14. Kovac D., Masek P., Hosek J.: Simulation-Based Study on Capacity Performance of 4G Mobile Network for M2M Services, in the International Conference “Technical Universities: Integration with European and World Systems of Education”, Izhevsk, Russia, April 2014.
  • 15. Masek P., Hosek J., Dubrava M.: Influence of M2M communication on LTE networks. In: The 10th International IEEE Conference, Zvule, Czech Republic, August 2014.
  • 16. Mehmood Y., Pötsch T., Marwat SNK, Ahmad F., Görg C. and Rashid I.: Impact of machine-to-machine traffic on LTE data traffic performance. In: Kotzab H., Panek J., Thoben K.D. (Eds.): Dynamics in Logistics, Proceedings of the 4th International Conference LDIC, Bremen, Germany 2014, 259-270.
  • 17. Morela J.: Vibration of machines and diagnostics of their technical condition. Polish Society of Technical Diagnostics, Warsaw 1992.
  • 18. OREDA (2009), OREDA Reliability Data, OREDA Participants. Available from: Det Norske Veritas, NO 1322 Høvik, Norway, 4th Ed.
  • 19. Rausand M.: Risk assessment, Theory, Methods, and Applications. John Wiley & Sons, Inc., 2011.
  • 20. Setlak L., Kowalik R., Lusiak T.: Practical use of composite materials used in military aircraft, Materiale 2021, 14(17), https://www.mdpi.com/1996-1944/14/17/4812.
  • 21. SimuLTE Modeler Version (0.9.1). Accessed: 21-July-2018, http://www.simulte.com.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0c2b1000-c062-4f39-8ada-81fcb77a648d
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