INFORMATION TECHNOLOGIES FOR MANAGING AVIATION SYSTEMS
Keywords:flight safety, risks, human factor, biomedical indicators, measurement process, quantitative assessment
The proposed work analyzes the peculiarities of implementing a proactive approach in aviation. Within the framework of this approach, the human factor is considered as the cause of the occurrence of a dangerous event. An analysis of decision-making features was carried out to determine the possibilities of increasing the reliability of decision-making in aviation. The probability of occurrence of a dangerous event, the trigger of which is the human factor, is proposed to be determined based on the assessment of the functional state of the operator based on the information parameters of the cardiovascular system. The paper proposes an approach to determining the informativeness of parameters that directly depend on the number of measurements of these parameters. It is proposed to increase the reliability of decision-making regarding the state of the object not by increasing the number of measurements, but by additional processing of already measured information parameters, i.e. obtaining secondary information. As an example, the results of measurements of the RR intervals of the electrocardiogram by methods of nonlinear dynamics, namely Poincaré maps, were processed. The use of nonlinear dynamics methods to the already measured parameters of the cardiovascular system can provide an increase in the amount of information about the state of the operator and provide a new understanding of changes in the parameters of the cardiovascular system in hidden physiological states, providing additional prognostic information and complementing the traditional analysis in the time and frequency domains. The methods of nonlinear dynamics provide additional and independent information about the physiological, as well as about the hidden physiological response to the destabilizing factors. In the paper, as an example for processing already existing informational parameters of RR intervals of the electrocardiogram, their projection in phase space was carried out using Poincre maps to increase the informativeness of heart rate variability \. RR intervals are presented as a time series, and a Poincaré map allows the estimation of heartbeat dynamics based on a simplified phase space embedding. The use of Poincaré maps, as one of the methods of nonlinear dynamics, allows qualitative and quantitative analysis of cardiac signals, which reflects data variability. The “3D Poincaré map” obtained in the work have an advantage in the implementation of their construction and can be used to illustrate such properties as non-stationarity and multistability, which are important for understanding the dynamics of the physiological regulation system in the presence of destabilizing factors. In addition, it is possible to reveal unexpected regularities in the structure of the data, which makes this method useful for research studies, simplifying the formation of hypotheses, the development and verification of mathematical/physiological models.
Annex 18 — The Safe Transport of Dangerous Goods by Air. 999 Robert-Bourassa Boulevard, Montréal, Quebec, Canada H3C 5H7. URL: http://caa.gov.by/uploads/files/ICAO-Pr19-ru-izd-2-2016.pdf (access date 22.04.2022)
Khrashchevskyi R.V., Ivanets O.B. Features of a proactive approach in the flight safety system. Science-Based Technologies. 2021. N4(52). P.364-372. ISSN 2075-078. https://doi.org/10.18372/2310-5461.52.16383
Arcúrio Michelle Security Culture and Human Factors . Global Aviation Security Symposium (AVSEC2020). Virtual Symposium is “Improving Security Culture by Connecting the Dots”. (18 december 2020 )
The European Plan for Aviation Safety (EPAS 2020-2024). URL: https://www.easa.europa.eu/sites/default/files/dfu/EPAS_2020-2024.pdf (access date 22.04.2022)
Manual of Air Safety (MAS) Military Aviation Authority. URL: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/912759/MAS_Issue_7.pdf. (access date 22.04.2022)
Гончаренко Є. Культура безпеки польотів державної авіації України. Наука і оборона. 2019. № 1. C. 36-39. https://doi.org/10.33099/2618-1614-2019-6-1-36-39.
Ivanets O., Morozova I., Burichenko M., Kvach Y. Actual aspects of flight safety on the basis of measuring electrical indicators. 2021 XXXI International Scientific Symposium Metrology and Metrology Assurance (MMA). 2021. Publisher: IEEE. https://doi.org/10.1109/MMA52675.2021.9610872
Наказ Державної авіаційної служби України 06 березня 2020 р. №391. URL: https://avia.gov.ua/wp-content/uploads/2016/01/Metodichni-rekomendatsiyi-Metodologiya-otsinyuvannya-SU-nakaz-391.pdf (access date 22.04.2022)
Richman J.S., Moorman J.R. Physiological time-series analysis using approximate entropy and sample entropy. American Journal of Physiology. Heart and Circulatory Physiology. 2000. Vol. 278 (6). H2039–49. https://doi.org/10.1152/ajpheart.2000.278.6.H2039
Іванець О.Б., Буриченко М.Ю. Шляхи зменшення невизначеності прогнозу стану організму людини при нейромережевому моделюванні. Системи обробки інформації. 2012. №1(99). С.86-90.
Kuzmin V., Zaliskyi, M., Odarchenko, R., oth.. Method of Probability Distribution Fitting for Statistical Data with Small Sample Size. 2020 10th International Conference on Advanced Computer Information Technologies, ACIT 2020 - Proceedings, 2020, pp. 221–224
Romanenko Ye. O., Chaplay I. V. The essence and specifics of the services marketing system in the mechanisms of public administration. Actual Problems of Economics. 2016. No.12. P.81-89. http://nbuv.gov.ua/UJRN/ape_2016_12_11.
Shchapov P.F., Ivanets O.B., Sevryukova O.S. Dynamic properties of the time series of results of biomedical measurements. Science-based technologies. 2020. Vol 2 (46). P. 236 - 244. https://doi.org/10.18372/2310-5461.46.14811
Boyett M., Wang Y., D’Souza A. Cross Talk opposing view: Heart rate variability as a measure of cardiac autonomic responsiveness is fundamentally flawed. Physiol. 2019. Vol. 597. P.2599–2601. https://doi.org/10.1113/JP277501
Kantelhardt J.W., Zschiegner S.A., Koscielny-Bunde E., Havlin S., Bunde A., Stanley H.E. Multifractal detrended fluctuation analysis of nonstationary time series. Physica A: Statistical Mechanics and Its Applications. 2002. Vol. 87 (1). P. 87–114. https://doi.org/ 10.1016/s0378-4371(02)01383-3.
Henriques Teresa, Ribeiro Maria, Teixeira Andreia, Castro Luísa, Antunes Luís, Costa-Santos Cristina. Nonlinear Methods Most Applied to Heart-Rate Time Series: A Review. Entropy. 2020. Vol. 22. P. 309. https://doi.org/ 10.3390/e22030309
Agnieszka Kitlas Golińska. Poincar´e Plots in Analysis of Selected Biomedical Signals. Studies In Logic, Grammar And Rhetoric. 2013. Vol. 35 (48). P. 117-127. https://doi.org/ 10.2478/slgr-2013-0031
Hoshi R. A., Pastre C. M., Vanderlei L. C. M., Godoy M. F. Poincar´e plots indexes of heart rate variability: relationship with other nonlinear variables. Autonomic Neuroscience, Retrieved. 2013. (July 30, 2013). https://doi.org/10.1016/j.autneu.2013.05.004.
Eremenko V.S., Burichenko M.Yu., Ivanets O.B. Method of processing the results of measurements of medical indicators. Science-based technologies. 2020. Vol. 47. № 3. P. 392 - 398. https://doi.org/10.18372 / 2310-5461.47