Category: Issue 2 (200)

Issue 2 (200), article 5

DOI:https://doi.org/10.15407/kvt200.02.076

Cybernetics and Computer Engineering, 2020, 2(200)

Belov V.M., DSc (Medicine), Professor,
Head of the Department
e-mail: motj@ukr.net

Hontar T.M., PhD (Biology),
Senior Researcher
e-mail: gtm_kiev@ukr.net

Kobzar T.A., PhD (Medicine),
Senior Researcher
e-mail: kobzarta@ukr.net

Kozlovska V.O.,
Researcher
e-mail: vittoria13apr@gmail.com

International Research and Training Centre for Information Technologies
and Systems of the NAS and MES of Ukraine, Department of Application Mathematical and Technical Methods in Biology and Medicine
40, Glushkov av., Kyiv, 03187, Ukraine

HEALTH SELF-ESTEEM INFORMATION TECHNOLOGY
FOR REHABILITATION OF POST-TRAUMATIC STRESS DISORDER

Introduction. Contemporary research aimed at preserving and maintaining human health is based on the use of intellectual information technology, developed on methodology of a systematic approach to the category of health as a trinity of its physical, mental and social aspects. The importance of a comprehensive approach to human health becomes especially evident in the case of breach of the harmonious interaction of the human body and personality with the environment in the example of post-traumatic stress disorder. At the present stage of economic and political development of the state, the factor of negative psychogenic impact on the health of the population has significantly increased. The creation of information technology for the assessment of health and rehabilitation of a person having post-traumatic stress disorder (PTSD) would make it possible to turn the rehabilitation process into a manageable and controlled one.

The purpose of the paper is to determine the information structure of post-traumatic stress disorder and the formation of main provisions of information technology of health self-assessment for the rehabilitation of post-traumatic stress disorder.

Results. The paper deals with the assessment of integral health level for people having PTSD and psychological and social rehabilitation of such patients. General features of psychogenic disorders and theoretical features of formation of post-traumatic stress disorder are discussed, taking into account the possibilities of the information approach. Information field of post-traumatic syndrome in general is offered, where on the basis of available literature the main exogenous stressors, protective variants of reactions of the organism and personality, variants of addictive behavior of persons suffering from post-traumatic stress disorder are determined. Information technology of self-assessment of physical, mental and social state of health by means of developed hardware-software “Express diagnostics of health” complex enabling to estimate integral health and its components using the applied questionnaire, is offered. The mental status of health determines the properties and strength of personality, which are important to consider and rely on in the process of rehabilitation of patients with post-traumatic stress disorder.

Conclusions. Availability of objective and subjective data on the state of health of a person with PTSD, including certain quantitative criteria for its health, as well as taking into account the information field of, which combines main exogenous stressors and their corresponding protective variants of organism reactions and variants of addictive behavior, gives the chance to analyze in detail its condition and compose individual programs of rehabilitation actions. At the same time, knowledge of a person’s character makes it possible with high probability to predict and, thus, adjust his expected actions and deeds. The use of developed hardware and software modules for health assessment in the case of PTSD will favor the effectiveness of rehabilitation measures.

Keywords: information technology, health self-assessment, mental health, personality character, methods of testing and diagnostics, post-traumatic stress disorder, psychosocial and social rehabilitation.

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REFERENCES

1. Diagnostic criteria DSM-III-R. Kyiv: Abris, 1995, 272 p. (in Ukrainian).
2. Chaban O.S. Frankova I.A. Current trends in the diagnosis and treatment of post-traumatic stress disorder. NeuroNews: Psychoneurology and Neuropsychiatry. 2015, No. 2 (66), pp. 8–18. (in Russian).
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8. World Bank experts have assessed the mental health sector in Ukraine – a statement from the Ministry of Health of Ukraine dated November 3, 2017. URL:  https://moz.gov.ua/article/news/eksperti-svitovogo-banku-dali-ocinku-galuzi-psihichnogo-zdorovja-v-ukraini. (in Ukrainian).
9. Comer Ronald. Pathopsychology of behavior: disorders and pathologies of the psyche / trans. with English, 4th ed., International. St. Petersburg: PRIME EUROZNAK, Moscow: OLMA-PRESS, 2005, 638 p. (in Russian).
10. Jaspers Carl. General psychopathology. Moscow: Practice, 1997, 1056 р. (in Russian).
11. Belov V.M., Kotova A.B. Human health: challenges, methods, approaches. Kyiv: Naukova Dumka, 2017, 132 р. (in Russian).
12. Belov V.M., Kotova A.B., Pustovoit O.G. Method of standardized unification of different quality information: utility model patent № 11235. Bull. №12. Publ. 12/15/2005. (in Ukrainian).
13. Belov V.M., Kotova A.B., Dubovenko M. N., Kiforenko S.I. Computer program “System of express diagnostics of a state of health”: a certificate of registration of copyright law on the work №37242, Ukraine. – 04/03/2011. (in Ukrainian).
14. Zotov V.P., Antomonov Yu.G., Kotova A.B., Belov V.M. Introduction to Wellness Rehabilitation. Kyiv: Madekol, RSPFN “Medicine-Ecology”, 1995, 181 p. (in Russian).
15. Belov V.M. Structural and functional organization of the “I” system. Cybernetics and computing. 2006, Issue 152, pp.3-19. (in Russian).
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17. Belov V.M., Hontar T.M., Semchinskaya E.I. Taking into account the state of the characterological component of a person in the synthesis of health self-government programs. Cybernetics and computing. 2009, Issue. 158, pp.3-10. (in Russian).

Received 20.03.2020

Issue 2 (200), article 4

DOI:https://doi.org/10.15407/kvt200.02.059

Cybernetics and Computer Engineering, 2020, 2(200)

KOCHINA M.L.¹, DSc (Biology), Professor,
Head of the Medical and Biological
Basics of Sports and Physical Rehabilitation Department
e-mail: kochinaml@gmail.com

KOZAK L.M.², DSc (Biology), Senior Researcher,
Leading Researcher of the Medical Information Systems Department
e-mail: lmkozak52@gmail.com

YAVORSKY O.V.³, DSc (Medicine),
Professor of Ophthalmology Department

FIRSOV O.G.⁴, PhD (Engineering),
Chief Designer
e-mail: shagrath.hire@gmail.com

YEVTUSHENKO A.S.⁵, PhD (Medicine),
Ophthalmologist
e-mail: andrey-eye@yandex.ru

¹Petro Mohyla Black Sea National University
10, 68-Desantnykiv st., Mykolaiv, 54000, Ukraine
²International Research and Training Centre for Information Technologies and Systems of the National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine
³Kharkiv National Medical University,
4, Nauky av., Kharkiv, 61000, Ukraine
⁴ASTER-AITI, LTD
1, Aviation st., Kharkiv, 61166, Ukraine
⁵L.L. Hirschman Kharkiv city clinical hospital №14
5, Oles Honchar st., Kharkiv, 61000, Ukraine

MODEL AND METHOD FOR EVALUATION AND FORECAST
OF THE CHANGES OF VISUAL SYSTEM FUNCTIONAL STATE
IN CONSEQUENCE OF VISUAL WORK

Introduction. During mental work, 90% of information is perceived by the human visual system (VS), so the effectiveness of the activities depends on the quality of the VS functioning and the presenting of visual information, especially non-traditional forms (TV, personal computer monitor, miniature displays on mobile phones, e-books). Prolonged information overload can lead to the states such as chronic stress, chronic fatigue syndrome, neurosis, occupational burnout and asthenopia, which worsen the operator` functional state, affect the quality of work tasks performance, last a long time and require special correction and treatment.

The purpose of the paper is to develop a method for evaluating and predicting the operators` functional state based on a model for predicting changes of the VS state under the visual work, as well as to implement this method in clinical decision support system for analyze the SV states changes because of visual work.

Results. Two clusters have been identified according to the mechanisms of changes in the VS state due to visual work. A model for predicting these changes is developed based on a set of indicators of the SV functional state using the fuzzy clustering algorithm (c-means) and the fuzzy derivation system Sugeno. According to results of previous research and this forecast model, a method for assessing and forecasting the functional state of a operator and his visual system has been developed. The proposed method is implemented in clinical decision support system for analysis and prediction of changes of the operator’s VS state due to visual work.

Conclusions. Developed method and automated system allow to predict changes of VS state in the case of a given visual load, to compare the current functional state with the previous one, to obtain information about the effectiveness of the recommended preventive measures. Approbation of the developed system determined that the use of this method of operators` functional state assessment and prediction, as well as recommendations for individual correction of the existing state led to improving of visual function in 67% of patients, and reducing of overall complaints in 50%, visual complaints in 53%, eye complaints – in 40% of patients.

Key words: functional state of visual system, visual load, model for forecasting of VS state, asthenopia, fuzzy clustering, clinical decision support system

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REFERENCES

1 Kornyushina T.A. The role of accommodation in the occurrence of asthenopia. Biomechanics of the eye. 2007, Moscow, pp. 9-13. (in Russian)

2 Ovechkin I.G., Yudin V.E., Emelyanov G.A., Mironov A.V. A multidisciplinary approach to the correction of accommodation-refractive disorders in patients with visually-intense work. Ophthalmology. 2015, Vol. 12, no. 2, pp. 68-73. (in Russian)

3 Shapovalov S. L., Milyavskaya T. I., Ignatiev S. A. Accommodation of the eye and its disturbances. 2012, Moscow, 188 p. (in Russian)

4 Bali J., Navin N., Thakur B.R. Computer vision syndrome: A study of the knowledge, attitudes and practices in Indian Ophthalmologists. Indian J. Ophthalmol. 2007, Vol. 55, pp. 289-293.
https://doi.org/10.4103/0301-4738.33042

5 Rosenfield M. Computer vision syndrome: a review of ocular causes and potential treatments. Ophthalmic Physiol. Opt. 2011, Vol. 31 (5), pp. 502-515.
https://doi.org/10.1111/j.1475-1313.2011.00834.x

6 Zadeh L.A. Biological applications of the theory of fuzzy sets and systems. The Proceedings of an International Symposium on Biocybernetics of the Central Nervous System. 1969, Boston, pp. 199-206.

7 Folkard S., Robertson K., Spencer M. A fatigue/Risk Index to assess work schedules. Somnologie. 2007, Vol. 11, pp. 177-185.
https://doi.org/10.1007/s11818-007-0308-6

8 Rutkovskaya D., Pilinsky M., Rutkovsky L. Neural networks, genetic algorithms and fuzzy systems. 2006, Moscow, 452 p. (in Russian)

9 Cheremukhina O. M. Mathematical modeling and prediction of the extent of internal twigs. Likarska sprava. 2011, no. 1/2, pp. 75-81. (in Ukrainian)

10 Zadeh L.A. Fuzzy logic and approximate reasoning. Synthese APRIL/MAY. 1975, Vol. 30, no 3/4, pp. 407-428.
https://doi.org/10.1007/BF00485052

11 Lisboa P.J., Taktak A.F.G. The use of artificial neural networks in decision support in cancer: a systematic review. Neural. Networks. 2006, Vol. 19, no 4, pp. 408-415.
https://doi.org/10.1016/j.neunet.2005.10.007

12 Kalnish V.V., Firsov A.G., Shvets A.V., Yeshenko A.I. Features of the classification of the state of a human operator by means of fuzzy logic. Kibernetika i vycislitel’naa tehnika. 2011, Iss. 166, pp. 55-67. (in Russian)

13 De Rivercourt M., Kuperus M.N., Post W.J., Mulder L.J.M. Cardiovascular and eye activity measures as indeces for momentary changes in mental effort during simulated flight. Ergonomics. 2008, Vol. 51, No 9, pp. 1295-1319.
https://doi.org/10.1080/00140130802120267

14 Vilela M. A. P., Castagno V. D., Meucci R. D., Fassa A. G. Asthenopia in schoolchildren. Clin. Ophthalmol. 2015, Vol. 9, pp. 1595-1603.
https://doi.org/10.2147/OPTH.S84976

15 Kochina M.L., Saykovskaya L.F., Yavorsky A.V., Lad S.N. Approaches to modeling the functional state of the visual system. Kibernetika i vycislitel’naa tehnika. 2009, Iss. 158, pp. 19-27. (in Russian)

16 Kochina M.L., Kalimanov V.G. Classification of lesions of the oculomotor muscles using the apparatus of fuzzy logic. Kibernetika i vycislitel’naa tehnika. 2011, Iss. 166, pp. 97-107. (in Russian)

17 Rykov S.O., Cheremukhina O.M. New information systems in ophthalmology. Philate reading: materials of scientific-practical conference and ophthalmologists with international participation. 2012, Odessa, pp. 334-335. (in Ukrainian)

18 Kochina M.L., Kozak L.M., Evtushenko A.S. Analysis of changes in factor structures of indicators of a person’s functional state with different types of visual load. Bulletin of problems in biology and medicine. 2013, Vol. 1, Iss. 1. pp.41-45. (in Russian)

19 Leonenkov A. V. Fuzzy modeling in MATLAB and fuzzyTECH. 2005, St. Petersburg, 736 p. (in Russian)

20 Yager R., Filev D. Essential of Fuzzy Modeling and Control. 1994, NY: JohnWilley&Sons, 388 p.

21 Odinets Yu.V., Kharchenko T.V., Trindyuk Yu.S. The use of fuzzy logic in the diagnosis of pyelonephritis in children. Actual problems of conventional medicine. 2011, Iss. 4 (36), Part 1, pp. 63-68. (in Russian)

22 Open source software for numerical computation. URL: http://www.scilab.org/

23 Fuzzy Logic Tool box. URL : http://atoms.scilab.org/ toolboxes/sciFLT/0.4.7

24 Nathan A. NET and COM: The Complete Interoperability Guide. 2002, Indianopolis: Sams Publishing, 1579 p.

25 Fuzzy Logic Library for Microsoft Net (fuzzynet). URL: https://sourceforge.net/projects/fuzzynet.

26 Microsoft Access 2016 Runtime. URL: https://www.microsoft.com/uk-ua/download/details.aspx?id=50040

27 Antomonov M.Yu. Methodology for the formation of complex indicators in environmental and hygienic research. Hygiene and sanitation. 1993, no 7, pp. 20-22. (in Russian)

28 Antomonov M.Yu. Mathematical processing and analysis of biomedical data, 2nd ed. 2018, Kyiv: MEC “Medinform”, 579 p. (in Russian)

Received 03.01.2020

Issue 2 (200), article 3

DOI:https://doi.org/10.15407/kvt200.02.041

Cybernetics and Computer Engineering, 2020, 2(200)

GRITSENKO V.I., Corresponding Member of NAS of Ukraine,
Director of International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and MES of Ukraine
e-mail: vig@irtc.org.ua

VOLKOV O.Ye., 
Senior Researcher of the Intelligent Control Department
e-mail: alexvolk@ukr.net

BOGACHUK Yu.P., PhD. (Engineering),
Leading Researcher of the Intelligent Control Department
e-mail: dep185@irtc.org.ua

GOSPODARCHUK O.Yu., 
Senior Researcher of the Intelligent Control Department
e-mail: dep185@irtc.org.ua

KOMAR M.M., 
Researcher of the Intelligent Control Department
e-mail: nickkomar08@gmail.com

SHEPETUKHA Yu.M., PhD. (Engineering),
Leading Researcher of the Intelligent Control Department
e-mail: dep185@irtc.org.ua

VOLOSHENIUK D.O., 
Researcher of the Intelligent Control Department
e-mail: p-h-o-e-n-i-x@ukr.net

International Research and Training Center for Information Technologies and Systems of the National Academy of Sciences of Ukraine and of Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

INTELLECTUAL CONTROL, LOCALIZATION AND MAPPING
IN GEOGRAPHIC INFORMATION SYSTEMS
BASED ON ANALYSIS OF VISUAL DATA

Introduction. Nowadays, geoinformation systems (GIS) are widely used in transport, construction, navigation, geology, geography, military affairs, topography, economics and more.

Problem Statement. Modern GIS publications highlight a number of pressing issues regarding the need to develop technologies and methods for the rapid formation of spatial-temporal geoinformation data bases and dynamic mapping images. The process of prompt formation of cartographic images of the area of unmanned aerial vehicles (UAV) flights in GIS databases is based on the simultaneous solution of two problems – determining the location of UAV in space, as well as the formation of a mapping image of the area under study.

 The purpose of the paper is to descript the method of topographic clustering of the obtained photographic images of UAV flights, which allows to combine visual images due to the semantic search of their topographic similarity, in order to realize the visual localization of UAV and high-precision layout of the mapping image of the navigation environment in the operational GIS database.

Materials and methods. The research conducted is based on the technologies of intelligent processing of large arrays of video and photo data, the theory of automatic control, methods of image processing and recognition based on descriptors of special points, methods of computer vision, as well as on methods and algorithms of own development, theory of navigation and dynamics of UAV flight.

Results. Procedures of topographic clustering of visual images obtained with UAV are developed, which are used for cognitive detection, description and matching among the characteristic features of the navigation environment.

Conclusions. The formation of a mapping image of the area of the navigation environment using the proposed method of topographic clustering of visual images achieved a decimeter accuracy in spatial coordinates, allowing visual localization and mapping with a high level of accuracy.

Keywords: unmanned aerial vehicle, geoinformation system, information technology, computer vision, intelligent control, cartographic image, aerial photography.

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REFERENCES

1 Artes T., Cencerrado A., Cortes A., Margalef T. Real-time genetic spatial optimization to improve forest fire spread forecasting in high-performance computing environments. International Journal of Geographical Information Science. 2016, Vol. 30, No 3, pp. 594-611.
https://doi.org/10.1080/13658816.2015.1085052

2 Li J., Bi Y., Lan M., Qin H., Shan M., Lin F., Chen B.M. Real-time Simultaneous Localization and Mapping for UAV: A Survey. Proc. of International micro air vehicle competition and conference. 2016, Beijing, China, 2016, pp. 237-242.

3 Kozub, A. M., Suvorova, N. O., & Chernyavsky, V. M. (2011). Analiz zasobiv zboru informatsiyi dlya heohrafichnykh informatsiynykh system. Systemy ozbroyennya i viys’kova tekhnika. 2011, No 3, pp. 42-47. (In Ukrainian)

4 Gonzales D., Harting S. Designing Unmanned Systems with Greater Autonomy: Using a Federated, Partially Open Systems Architecture Approach. Santa Monica, Calif: RAND, 2014, 96 p.

5 Agunbiade O., Zuva T., A Review: Simultaneous Localization and Mapping in Application to Autonomous Robot. Preprints 2018. 2018050293 (doi: 10.20944/preprints201805.0293.v1).
https://doi.org/10.20944/preprints201805.0293.v1

6 Fuentes-Pacheco J., Ruiz-Ascencio J., Rendon-Mancha J.M. Visual simultaneous localization and mapping: a survey. Artificial Intelligence Review. 2015, Vol. 43, No1, pp. 55-81.
https://doi.org/10.1007/s10462-012-9365-8

7 Silpa C., Hartley R. Optimised KD-trees for fast image descriptor matching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2008, pp. 1-8.

8 Dufournaud Y., Schmid C., Horaud R. Image matching with scale adjustment. Computer Vision Image Understanding. 2004, No 93(2), pp. 175-194.
https://doi.org/10.1016/j.cviu.2003.07.003

9 Zhang W., Kosecka J. Image based localization in urban environments. Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission. 2006, Chapel Hill, USA, pp. 33-40.
https://doi.org/10.1109/3DPVT.2006.80

10 Schubert J., Brynielsson J., Nilsson M., Svenmarck P. Artificial Intelligence for Decision Support in Command and Control Systems. Proceedings of the 23rd International Command and Control Research & Technology Symposium “Multi-Domain C2”. 2018, Playa Vista, California, USA, pp. 18-33.

11 Bradski G., Kaehler A. Learning OpenCV. O’Reilly Media, 2008, 576 p.

Received 27.02.2020

Issue 2 (200), article 2

DOI:https://doi.org/10.15407/kvt200.02.027

Cybernetics and Computer Engineering, 2020, 2(200)

YERMAKOVA I.I., DSc (Biology), Professor
Leading Researcher
e-mail: irena.yermakova@gmail.com

NIKOLAENKO A.Y., PhD (Engineering),
Researcher
e-mail: n_nastja@ukr.net

BOGATONKOVA A.I., PhD (Engineering),
Senior Researcher
e-mail: bogatonkova@gmail.com

HRYTSAIUK O.V.,
Junior Researcher
e-mail: olegva11@gmail.com

KRAVCHENKO P.M.,
Senior Engineer
e-mail: paul.kravchenko@gmail.com

International Research and Training Center for Information Technologies and Systems of the National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, the Department of Complex Research of Information Technologies,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

INFORMATION TECHNOLOGY FOR PREDICTION
OF HUMAN STATE IN EXTREME ENVIRONMENTS

Introduction. Being in cold water refers to extreme effects. Due to its high thermal conductivity and heat capacity, water is an extreme factor for rapid cooling of the body. For the safe swimming and working of a man in cold water special protective equipment — wetsuits is used. The method of mathematical modeling makes it possible to study the processes of heat exchange between human and water environment, taking into account environmental conditions, level of physical activity and wetsuit characteristics.

The purpose of the paper is to develop information technology for evaluation and prediction of human thermophysiological state for safe staying in the water.  As a result computer module for influence of protective clothing on human thermal state has been developed.

Results. The information technology for prediction of human state in extreme conditions in water is proposed. The computer module for prediction and evaluation of human thermophysiological state in a wetsuit has been developed. This module is based on a complex of mathematical models of human thermoregulation in extreme environments. The adequacy of mathematical models is proved by comparing the modeling results with observations on people. This suggests that the information technology and computer module can be applied to perform theoretical and practical tasks related to human health in cold water.

With the help of the developed computer module modeling experiments of influence of the design of a wetsuit on the thermoregulation of person in water were held. Two wetsuits were researched: short sleeves and short trousers and long sleeves and long trousers. Were obtained the forecast and the analysis of thermophysiological state of swimming man, duration was one hour, speed was 1 m/s, temperature of water from 10 °C to 26 °C.

Conclusions. The information technology for predicting thermophysiological state of a man allows to investigate the influence of a protective suit of different design on the thermoregulation of a human body. It’s shown that the choice of wetsuit can be made only in combination with temperature of water and planned physical activity, otherwise mistakes can lead to a violation of thermal comfort in the case of human’ being in water.

Keywords: model of human thermoregulation, information technology, computer module, extreme conditions, water environment, wetsuit. 

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REFERENCES

1 American Red Cross. Swimming and Water Safety, 3rd ed. 2009, Chapter 3, pp. 43-64. ISBN 978-1-58480-446-8

2 Tipton M.J., Brooks C.J. The Dangers of Sudden Immersion in Cold Water. Survival at Sea for Mariners, Aviators and Search and Rescue Personnel. Brussels, Belgium, 2008, Chapter 3, pp. 1-10. ISBN 978-92-837-0084.

3 Tipton M., Bradford C. Moving in extreme environments: open water swimming in cold and warm water. Extreme physiology & medicine. 2014, Vol. 3, No 1, pp. 12.
https://doi.org/10.1186/2046-7648-3-12

4 Yermakova I., Montgomery L. Predictive Simulation of Physiological Responses for Swimmers in Cold Water. Proceedings of the 38th International scientific conference electronics and nanotechnology. Institute of Electrical and Electronics Engineers, Kyiv, Ukraine, 2018, pp. 292-297.
https://doi.org/10.1109/ELNANO.2018.8477523

5 Gavrilova O.E., Nikitina L.L. The choice of constructive decisions and polymeric materials for clothing used in the water. Vestnik of the Kazan Technological University. 2015, Vol. 18, No 13, pp. 153-155. (in Russian)

6 Gritsenko V., Yermakova I., Dukchnovskaya K., Tadejeva J. Dynamic models and information technologies for prediction of human vital functions. Control Systems and Computers. 2004, Vol. 2, pp. 56-60. (in Russian)

7 Enescu D. Models and Indicators to Assess Thermal Sensation Under Steady-State and Transient Conditions. Energies. 2019, Vol. 12, Iss. 5, No 841, pp. 1-43.
https://doi.org/10.3390/en12050841

8 Parsons K. Human thermal environments: the effects of hot, moderate, and cold environments on human health, comfort and performance. CRC press, 2002, 2nd Ed, 560 p.

9 Montgomery L.D. A model of heat transfer in immersed man. Annals of biomedical engineering. 1974, Vol. 2, No 1, pp. 19-46.
https://doi.org/10.1007/BF02368084

10 Miller N.C., Seagrave R.C. A model of human thermoregulation during water immersion. Computers in biology and medicine. 1974, Vol. 4, No 2, pp. 165-182.
https://doi.org/10.1016/0010-4825(74)90018-3

11 Tikuisis P., Gonzalez R.R., Pandolf K.B. Thermoregulatory model for immersion of humans in cold water. Journal of Applied Physiology. 1988, Vol. 64, No 2, pp. 719-727.
https://doi.org/10.1152/jappl.1988.64.2.719

12 Tikuisis P., Gonzalez R.R., Pandolf K.B. Prediction of human thermoregulatory responses and endurance time in water at 20 and 24 degrees C. Aviation, space, and environmental medicine. 1988, Vol. 59, No 8, pp. 742-748.

13 Yermakova I., Solopchuk Y. Computer model of human thermoregulation during water immersion. Kibernetika i vycislitelnaa tehnika. 2013, Vol. 172, pp. 39-48. (in Russian).

14 Wakabayashi H., Hanai A., Yokoyama S., Nomura T. Thermal insulation and body temperature wearing a thermal swimsuit during water immersion. Journal of physiological anthropology. 2006, Vol. 25, No 5, pp. 331-338.
https://doi.org/10.2114/jpa2.25.331

15 Toner M. M., Sawka M. N., Holden W. L., Pandolf K. B. Comparison of thermal responses between rest and leg exercise in water. Journal of Applied Physiology. 1985, Vol. 59, No 1, pp. 248-253.
https://doi.org/10.1152/jappl.1985.59.1.248

16 Yermakova I., Nikolaienko A., Tadeieva J., Montgomery L. Protective effect of wetsuits for swimmers in cold water: modelling results. Proceedings of the 7th European conference on protective clothing (ECPC 2016) (23th – 25th of May, Izmir). Izmir, Turkey. Izmir, Turkey, 2016, pp. 57-58.

Received 13.02.2020

Issue 2 (200), article 1

DOI:https://doi.org/10.15407/kvt200.02.005

Cybernetics and Computer Engineering, 2020, 2(200)

CHABANIUK V.S.,^1,2 PhD (Phys.&Math.),
Senior Researcher of the Cartography Department,
Institute of Geography, National Academy of Sciences of Ukraine,
Director of “Intelligence Systems-GEO” LLC,
email: chab3@i.ua, chab@isgeo.kiev.ua

KOLIMASOV I.M.,²
Head of Production of “Intelligence systems-GEO” LLC,
email: kolimasov@ukr.net

¹ Institute of Geography, National Academy of Sciences of Ukraine
44, Volodymyrsk str., 01030, Kyiv, Ukraine
²“Intelligence systems-GEO” LLC,
6/44, Mikilsko-Slobidska Str., 02002, Kyiv, Ukraine.

ANALYSIS OF THE PRACTICAL USE OF GEOINFORMATION SYSTEMS FOR TERRITORIAL MANAGEMENT AND DETERMINATION OF THEIR CRITICAL PROPERTIES

Introduction. The practical experience of creation, implementation and operation of geoinformation system (GIS) for territory management allows to identify their critically important properties. GIS with critical properties do not fit the conventional definition because they are more advanced systems. Special attention to critical properties helps to reduce the risks involved in the development and implementation of such GIS, as well as to increase the effectiveness of their use for territory management.

The purpose of the paper is to analyze the use of GIS developed by the authors for the management of large territories and to determine their main critical properties. Critical GIS properties are being sought to manage territories that: 1) repeat for all such GIS, 2) differentiate them from conventional GIS, 3) must be taken into account when creating new GIS.

Results. The critical properties that are mandatory also for modern GIS for territory management are as follow: 1) the availability of education-scientific, production and management components, 2) the availability of a relatively independent atlas solution, 3) the obligation to use portals, 4) the need to supplement the territory modeling of their metamodeling.

Conclusions. Abductive inferences after analyzing the practical experience of creation, implemention and operation of GIS for territory management allow to confirm the presence of critical properties of GIS.  Without any such property, we can speak about a corresponding critical shortcoming of the GIS project, and this project is likely to be a failure.

Keywords: geoinformation system, territory management, spatial data, abduction, critical property

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Received 10.03.2020