Issue 2 (208), article 5

DOI:https://doi.org/10.15407/kvt208.02.082

Cybernetics and Computer Engineering, 2022, 2(208)

PANAGIOTIS KATRAKAZAS, Ph.D., Research Area Manager
ORCID: 0000-0001-7433-786X
e-mail: p.katrakazas@zelus.gr

ILIAS SPAIS, Ph.D., Senior Project Manager
Researcher ID: https://www.semanticscholar.org/author/I.-Spais/1885927
e-mail: ilias.spais@zelus.gr

Zelus,
Tatoiou 92,
14452, Metamorfosi, Athens, GR

BLUEPRINTS ELICITATION FRAMEWORK FOR AN OPEN ACCESS
PAN-EUROPEAN NEURO-IMAGING ONLINE CENTRE

Introduction. Recent infrastructural endeavours in the field of neuroscience aimed at data integration and sharing and availability of research output. This approach recognized that opening experimental results produces significant gains for science advancement. Nonetheless, this leaves a large part of the grassroots neuroscience community underutilized: access to neuroimaging infrastructures remains locally restricted, obstructing data acquisition and the means to investigate novel hypotheses.

Purpose. Within our paper we seek to address this gap by providing the blueprints for a delocalized e-neuroscience centre, opening the access to functional neuroimaging acquisition systems at a pan-European level. This aim will be achieved by building operational interoperability, standardizing, and integrating the services of neuroscience centres across Europe and the development of a virtual environment allowing all European researchers to acquire state-of-the-art neuroimaging data, exploiting the principles of the European Charter for Access to Research Infrastructures

Results. The implementation of all necessary actions for the harmonization and interoperability of the experimental procedures of the labs entail standardization of protocols, procedures in the form of consensus-based guidelines, harmonization of hardware and software set-up and availability across laboratories, as well as adopting of common standards and formats for acquired data and metadata structures.

Conclusion. Consistent and streamlined mobility processes aim to become a blueprint for networking of the overall neuroscience community. The harmonized process framework presented in this paper can facilitate better use from current and future neuroscience projects. Data economies of scale and recruitment streamlining will put local EU and international funds to better use than the now dispersed efforts. This will lead to more successful projects and better pacing for EU neuroscientific communities in the international stage.

Keywords: multi-centre interoperability, operational harmonisation, neuroimaging, sharing infrastructures, open access framework.

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21. Rizzo F., Deserti A., and Komatsu T., ‘Implementing social innovation in real contexts’, Int. J. Knowl.-Based Dev., vol. 11, no. 1, pp. 45–67, 2020.

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A Strategic Approach to Innovation’, Br. J. Manag., vol. 26, no. 3, pp. 463–483, 2015, doi: 10.1111/1467-8551.12087.

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Received 23.05.2022

Issue 2 (208), article 4

DOI:https://doi.org/10.15407/kvt208.02.060

Cybernetics and Computer Engineering, 2022, 2(208)

ARALOVA N.I.1, DSc (Engineering), Senior Researcher, 
Senior Researcher of Optimization of Controlled Processes Department,
ORCID 0000-0002-7246-2736,
e-mail: aralova@ukr.net

BELOSHITSKIY P.V.2, DSc (Medicine)
Professor of Biological Faculty
ORCID 0000-0002-6058-3602
e-mail: bilosh827@ukr.net

ZUBIETA-CALLEJA G.3 M.D. Professor
Director
ORCID: 0000-0002-4283-6514
e-mail: zubieta@altitudeclinic.com

ARALOVA A.A.1 PhD (Mathematics)
Researcher of the Department of Methods for Discrete Optimization,
Mathematical Modelling and Analyses of Complex Systems
ORCID 0000-0001-7282-2036
email: aaaralova@gmail.com

1Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine,
40, Acad.Glushkov av., 03187, Kyiv, Ukraine

2Pavlo Tychyna Uman State Pedagogical University,
2, Sadova str, 20300, Uman, Chercassy distr., Ukraine

3High Altitude Pulmonary and Pathology Institute
HAPPI-IPPA La Paz, Bolivia

AUTOMATED INFORMATION SYSTEM FOR THE EVALUATION OF CLIMBERS’ PERFORMANCE UNDER CONDITIONS OF EXTREMELY LOW pO2 OF INHALED AIR

Introduction. Currently, as a result of ever-increasing intensity of human activity, unfavorable environment, the need to perform work in various extreme disturbances, significantly increase physical, mental and emotional stress on the human body, leading to pronounced changes in functional systems. Therefore, the task of studying the adaptation of the human body to work in extreme environments is urgent. The work of climbers is a fairly adequate model for studying the combined effects of hypobaric hypoxia and exercise hypoxia. The need to process large amounts of information necessitates the use of modern computer technology that allows the training process in the training of climbers, which would repeatedly, almost in real time to speed up the processing of survey data and accumulate for further use in determining current status and forecasting regulatory reactions of the body to external and internal disturbances

The purpose of the paper is to develop an automated information system of functional diagnostics using the model of regulation of oxygen regimes of the body and its practical application in the study of highly qualified climbers

Methods. Programming methods for creating an automated information system and methods of functional diagnostics.

Results. On the basis of the model of regulation of oxygen regimes of the organism the automated information system for functional diagnostics of the persons who are in the conditions of extreme disturbances is constructed. The results of approbation of the offered software for research of group of highly skilled climbers are resulted.

Conclusions. The proposed software allows you to use a model of oxygen regimes of the body in real time, i.e. repeatedly accelerates the processing of data obtained during the survey of athletes, allows centralized collection of information for its pre-processing, storage and collective use, allows you to compare the basic parameters characterizing the functional respiratory system during natural sports activities and obtained during ergometric loading,

Key words: methods of functional diagnostics, highly qualified climbers, mathematical model of regulation of oxygen regimes of the organism, human adaptation to work in extreme environment, hypoxibritic hypoxia

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Received 19.01.2022

Issue 2 (208), article 3

DOI:https://doi.org/10.15407/kvt208.02.044

Cybernetics and Computer Engineering, 2022, 2(208)

BONDAR S.O., PhD student,
Researcher of the Intelligent Control Department
ORCID: 0000-0003-4140-7985
e-mail: orangearrows@bigmir.net

SHEPETUKHA Yu.M., PhD (Engineering), Senior Researcher
Acting Head of the Intelligent Control Department
ORCID: 0000-0002-6256-5248
e-mail: shepetukha@irtc.org.ua

VOLOSHENYUK D.O., PhD (Engineering),
Senior Researcher of the Intelligent Control Department
ORCID: 0000-0003-3793-7801
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 Ministry of Education and Science of Ukraine.
40, Akad. Glushkov av., Kyiv, 03680, Ukraine.

USING OF HIGH-QUALITY POSITIONING TOOLS FOR HYBRID UNMANNED AERIAL VEHICLES AUTOMATIC CORRECTION UNDER THE LIMITED SPACE CONDITION

Introduction. Original class of hybrid unmanned aerial vehicles is considered for multitask mission accomplishment at this article. Advantages of such vehicles usage for purposes that are always done by several different agents are considered. Perspective of the position precisioning for different tasks that could be done by unmanned aircrafts is analyzed.

The purpose of the paper is to universalize the process of surveillance, photo and video data collection and other missions that is provided by unmanned aerial vehicles today. The action of data precision during some periods of the misson accomplishment and increased specification for main targets of the mission could demonstrate brand new vector of the unmanned aerial vehicle usage and creation of the brand new domains for the unmanned aerial vehicles. Complex data gathering could help to avoid extra mediators and could simplify data processing on the next stages and also could do such data much more precise.

Results. The usable scenario of route for hybrid unmanned aerial vehicle and the model of it could be a proof of universal multitask unmanned aerial vehicle utilization. Such scenario unites several information missions of different scale and could provide data for several data centers that can use it for defferent problem solving just from one flight. Also it proves that utilization of such aircraft with an additional onboard precision block could be the next step at the mapping and digitalizing domains. Financial analysis of the market is provided for demonstration of the fact that such hybrid aircraft complex system would provide such scale as well as attention to the object details but be much cheaper then mapping and surveillance systems that are already existing.

Conclusion. A need for optimization of some problems that could be achieved by unmanned aerial vehicles leaded to the usage of hybrid vehicles that were represented at the article. Complex design of such an aircraft could be a collateral disadvantage but the whole influence of the hybrid UAV usage for different tasks would optimize a lot more processes, devices and unnecessary equipment that would be needed for a large list of tasks at each domain UAVs are using right now from surveillance to agricultural tasks. Model of different scale purpose universal hybrid unmanned aerial system is a proof of the possibility to use just one single aircraft for a complex mission that needs different set of capabilities, features and equipment. Also such aircraft could provide much more certain results of missions and do it at lower price. Further developments could provide information about the most effective hybrid UAV type for such type of missions and provide game changing rules to the digitalizing and surveillance processes because of the new information gathering way.

Keywords: unmanned aerial vehicle, hybrid vehicle, positioning, multipurpose flight.

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5. Makeflyeasy Freeman 2300 Tilt VTOL Aerial Survey Carrier Span Fpv Rc Fix-wing Model drone Wing 2300mm UAV mapping Long range pryce. URL: HYPERLINK “https://www.uavmodel.com/products/makeflyeasy-freeman-2300-tilt-vtol-aerial-survey-carrier-span-fpv-rc-fix-wing-model-drone-wing-2300mm-uav-mapping-long-range” https://www.uavmodel.com/products/makeflyeasy-freeman-2300-tilt-vtol-aerial-survey-carrier-span-fpv-rc-fix-wing-model-drone-wing-2300mm-uav-mapping-long-range

6. Grytsenko V.I., Volkov O.Ye., Komar.M.M. et al. Modern unmanned aerial vehicle automatic control systems intellectualization. Cybernetics and Computer Engineering Journal. 2018, № 1, pp. 45–59. URL: http://nbuv.gov.ua/UJRN/Kivt_2018_1_4. (in Ukrainian)

7. Volkov O.Ye., Grytsenko V.I., Komar M.M. Integral Adaptive Autopilot for an Unmanned Aerial Vehicle. AVIATION: Scientific journal: scientific article. Vilnius, Lithuania, 2018, Vol. No 22, pp. 129–195.

8. Makeflyeasy Freeman 2300 Specification & Options URL: https://aliexpress.com/ item/10000223137957.html

Received 06.04.2022

Issue 2 (208), article 2

DOI:https://doi.org/10.15407/kvt208.02.030

Cybernetics and Computer Engineering, 2022, 2(208)

Savchenko-Synyakova Ye.A., PhD (Engineering),
Senior Researcher of the Department for Information
Technologies of Inductive Modeling
https://orcid.org/0000-0003-4851-9664
e-mail: savchenko_e@meta.ua

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,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

COMPARATIVE ANALYSIS OF MACHINE LEARNING METHODS AND OTHER DIRECTIONS OF ARTIFICIAL INTELLIGENCE

Introduction. Nowadays, the application of machine learning methods and tools is developing very rapidly, given the overall automation and digitalization. The use of machine learning methods and tools for modeling complex processes makes it possible to solve problems that were previously difficult or impossible to solve.

However other methods of mathematical modeling also make it possible to solve the problem of constructing a model based on a sample of experimental data. The task was to compare various scientific areas of artificial intelligence, such as machine learning, mathematical modeling, statistics, data mining and inductive modeling in terms of building mathematical models, to find out what common and distinctive features they have.

The purpose of the paper is a comparative analysis of the areas of mathematical modeling, statistics and machine learning. And also compare the methods of inductive modeling and inductive generation of models.

Results. A comparative analysis of machine learning and other approaches to solving artificial intelligence problems was carried out.

Conclusion. The conducted analysis showed that the machine learning tasks of mathematical (statistical) modeling are close, but not the same, and it is difficult to draw a hard line between them. They can be distinguished by the purpose, the ability to check or interpret the obtained results.

Keywords: machine learning, mathematical modeling, statistics, inductive approach, inductive generation of models.

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REFERENCES

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2. Bzdok, D., Altman, N. & Krzywinski, M. Statistics versus machine learning. Nat Methods. 15, pp. 233–234 (2018). https://doi.org/10.1038/nmeth.4642.

3. Alber, M., Buganza Tepole, A., Cannon, W.R. et al. Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences. npj Digit. Med. 2, 115 (2019). HYPERLINK “https://doi.org/10.1038/s41746-019-0193-y” https://doi.org/10.1038/s41746-019-0193-y.

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Received 22.04.2022

Issue 2 (208), article 1

DOI:https://doi.org/10.15407/kvt208.02.005

Cybernetics and Computer Engineering, 2022, 2(208)

RACHKOVSKIJ D.A.1,2, DSc (Engineering),
Chief Researcher, Dept. of Neural Information Processing Technologies,
Visiting Professor, Dept. of Computer Science, Electrical and Space Engineering,
https://orcid.org/0000-0002-3414-5334
e-mail: dar@infrm.kiev.ua

GRITSENKO V.I.1, Corresponding Member of NAS of Ukraine,
 Directorate Adviser,
ORCID ID 0000-0002-6250-3987
e-mail: vig@irtc.org.ua

VOLKOV O.E.1, PhD (Engineering), 
Director,
https://orcid.org/0000-0002-5418-6723
e-mail: alexvolk@ukr.net

GOLTSEV A.D.1, PhD (Engineering), Senior Researcher,
Acting Head of the Dept. of Neural Information Processing Technologies,
https://orcid.org/0000-0002-2961-0908
e-mail: root@adg.kiev.ua

REVUNOVA E.G.1, DSc (Engineering),
Senior Researcher, Dept. of Neural Information Processing Technologies,
https://orcid.org/0000-0002-3053-7090
e-mail: egrevunova@gmail.com

KLEYKO D.3, PhD (Computer Science), Researcher,
https://orcid.org/0000-0002-6032-6155
e-mail: denis.kleyko@ri.se

LUKOVICH V.V.1 Researcher of the Dept. of Neural Information Processing Technologies
ORCID ID 0000-0002-3848-4712
e-mail: vvl97@ukr.net

OSIPOV E.2, PhD (Computer Science), Professor,
https://orcid.org/0000-0003-0069-640X
e-mail: evgeny.osipov@ltu.se

1 International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and of the MES of Ukraine, 40, Acad. Glushkova av., Kyiv, 03680, Ukraine

2 Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology, 971 87 Lulea, Sweden

3 RISE Research Institutes of Sweden AB, 164 40 Kista, Sweden

NEURAL DISTRIBUTED REPRESENTATIONS FOR ARTIFICIAL INTELLIGENCE AND MODELING OF THINKING

Introduction.Current progress in the field of specialized Artificial Intelligence is associated with the use of Deep Neural Networks. However, they have a number of disadvantages: the need for huge data sets for learning, the complexity of learning procedures, excessive specialization for the training set, instability to adversarial attacks, lack of integration with knowledge of the world, problems of operating with structures known as binding or composition problem. Overcoming these shortcomings is a necessary condition for advancing from specialized Artificial Intelligence to general one, which requires the development of alternative approaches.

The purpose of the paper is to present an overview of research in this direction, which has been carried out at the International Center for 25 years. The approach being developed stems from the ideas of N. M. Amosov and his scientific school. Connections to the Hyperdimensional Computing (HDC) and Vector Symbolic Architectures (VSA) field as well as to current brain research are also provided.

Results. The concept of distributed data representation is outlined, including HDC/VSA that are capable of representing various data structures. The developed paradigm of Associative-Projective Neural Networks is considered: codevector representation of data, superposition and binding operations, general architecture, transformation of data of various types into codevectors, methods for solving problems and applications.

Conclusion. An adequate representation of data is one of the key issues within the Artificial Intelligence. The main area of research reviewed in this article is the problem of representing heterogeneous data in Artificial Intelligence systems in a unified format based on modeling the neural organization of the brain and the mechanisms of thinking. The approach under development is based on the hypothesis of distributed representation of information in the brain and allows representing various types of data, from numeric values to graphs, as vectors of large but fixed dimensionality.

The most important advantages of the developed approach are the possibility of natural integration and efficient processing of various types of data and knowledge, a high degree of parallel computing, reliability and resistance to noise, the possibility of hardware implementation with high performance and energy efficiency, data processing based on associative similarity search — similar to how human memory works. This allows one to unify the methods, algorithms, and software and hardware for Artificial Intelligence systems, increase their scalability in terms of speed and memory with an increase in data volume and complexity. 

The research creates the basis for overcoming the shortcomings of current approaches to the specialized Artificial Intelligence based on Deep Neural Networks and paves the way for the creation of Artificial General Intelligence.

Keywords: distributed data representation, associative-projective neural networks, codevectors, hyperdimensional computing, vector symbolic architectures, artificial intelligence.

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Received 17.03.2022

Issue 2 (208)

DOI:https://doi.org/10.15407/kvt208.02

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TABLE OF CONTENTS:

Informatics and Information Technologies:

Rachkovskij D.A., Gritsenko V.I., Volkov O.Ye., Goltsev A.D., Revunova E.G., Kleyko D., Lukovich V.V., Osipov E.
Neural Distributed Representations for Artificial Intelligence and Modeling of Thinking

Savchenko-Synyakova Ye.A.
Comparative Analysis of Machine Learning Methods and Other Directions of Artificial Intelligence

Intelligent Control and Systems:

Bondar S.O., Shepetukha Yu.M., Voloshenyuk D.O.
Using of High-Quality Positioning Tools for Hybrid Unmanned Aerial Vehicles Automatic Correction Under the Limited Space Condition

Medical and Biological Cybernetics:

Aralova N.I., Beloshitskiy P.V., Zubieta-Calleja G., Aralova A.A.
Automated Information System for the Evaluation of Climbers’ Performance Under Conditions of Extremely Low pO2 of Inhaled Air

Katrakazas P., Spais I.
Blueprints Elicitation Framework for an Open Access Pan-European Neuro-Imaging Online Centre

Issue 1 (207), article 7

DOI:https://doi.org/10.15407/kvt207.01.087

Cybernetics and Computer Engineering, 2022, 1(207)

Vovk М.І., PhD (Biology), Senior Researcher,
Head of the Department of Bioelectrical Control & Medical Cybernetics
ORCID: 0000-0003-4584-9553
e-mail: vovk@irtc.org.ua; imvovk3940@gmail.com

Kutsiak О.А., PhD (Engineering),
Senior Researcher of the Department of Bioelectrical Control & Medical Cybernetics
ORCID: 0000-0003-2277-7411
e-mail: spirotech85@ukr.net

International Research and Training Center
for Information Technologies
and Systems
of the NAS of Ukraine and of MES of Ukraine,
40, Acad. Hlushkov av. Kyiv, 03187, Ukraine

INFORMATION TECHNOLOGIES FOR MUSCLE FUNCTIONS CONTROL. RETROSPECTIVE ANALYSIS AND DEVELOPMENT PROSPECTS

Introduction. The research on muscle functions control is determined not only by scientific interest but also by practical necessity. 

The purpose of the paper is to conduct a retrospective analysis of the synthesis of information technologies for the control of human muscle functions for their recovery, correction or training.

Results. The evolution of the synthesis of science-intensive information technologies for muscle functions controlling with the purpose for recovering, correcting or training them on the basis of external control circuits is shown. The informative and energy myostimulation signals play the role of these loops. And the signals come from electronic software devices or information software and hardware complexes. The main classes of the first generation of such devices as open (“MIOTON”), adaptive (“MIOSTIMUL”), and modern — “TRENAR” are considered. The devices contain a set of basic software modules for activating the patient reserves to recover the muscle activity depending on the motor functions state and the patient general state. The new patented technology for oral speech recovery after stroke based on training the fine motor skills of the hand is considered. The new information technology of digital medicine “AI-REABILITOLOG” is presented. This technology for information assistance to user (physician) in making diagnostic and treatment decisions on rehabilitation of motor and speech functions uses artificial intelligence tools — specialized software modules for creating the personalized training plan of extremities, fine motor skill of the hand, in particular for oral speech recovery, and the gait on the results of their disorders quantitative assessment. The results of practical application, the advantages of the developed information technologies are presented. The prospects for their development are considered.

Conclusions. The main principles for synthesis of science-intensive information technologies for muscle functions controlling in order to recover, correct or train them on the basis of external control circuits are a combination of physical and cognitive influences, active participation of the subject in training procedures and their self-control.

Keywords: information technologies, digital medicine, control, myostimulation devices, muscle functions, movements, speech, diagnostics, rehabilitation, stroke, personalized quantitative assessment, criteria, artificial intelligence, software module, structural and functional model

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REFERENCES
1. Inventor’s certificate. The method of motor control / L. Aleev, S. Bunimovich (USSR); No 1019769/31-16; published 29.12.66, Bull. No 2. (in Russian).

2. Aleev L.S. Bioelectrical system “Mioton” and motor functions of a person. Bull. of AS of USSR. 1969. Issue 4. pp. 70-80 (in Russian).

3. Aleev L.S., Vovk M.I., Gorbanev V., Shevchenko A.B. “Mioton” in motor control. Kiev: Nauk. dumka, 1980. 142 p. (in Russian).

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5. Inventor’s certificate. Multichannel device for adaptive bioelectrical motor control of a person / L. Aleev, M. Vovk, V. Goranev, A. Shevchenko (USSR); No 929 054; 23.05.1982. (in Russian).

6. Inventor’s certificate. Multichannel device for adaptive bioelectrical motor control of a person / L. Aleev, M. Vovk, V. Goranev, A. Shevchenko (USSR); No 976 952; 03.08.1982. (in Russian).

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8. Gritsenko V.I. Vovk M.I., Kotova A.B., Kiforenko S.I., Belov V.M. Information technologies in biology and medicine. Course of lectures. Kyiv: Naukova Dumka, 2007. 382p. (In Ukrainian)

9. Vovk M.I., Kutsyak O.A. Software module for personal diagnostics of motor functions after stroke. Cybernetics and Computer Engineering. 2019. No 4 (198). pp. 62-77
https://doi.org/10.15407/kvt198.04.062

10. Patent. A method of treating speech disorders / M.I. Vovk, Ye.B. Halian, O.M. Pidopryhora (Ukraine); No 111388; publshed 25.04.2016, Bulletin no 18 (in Ukrainian)

11. Vovk, M.I., Halian, Ye.B., Kutsiak, O.A. Computer Software & Hardware Complex for Personal Oral Speech Restoration after a Stroke. Sci. innov. 2020. Vol. 16, No 1(91). pp. 54-68. https://doi.org/10.15407/scine15.05.054

12. Vovk M.I., Kutsyak O.A. Software module for personal diagnostics of motor functions after stroke. Cybernetics and Computer Engineering. 2019. No 4 (198). pp. 62-77
https://doi.org/10.15407/kvt198.04.062

13. Vovk M.I., Kutsiak O.A., Lauta A.D., Ovcharenko M.A. Information Assistance of Researches on the Dynamics of Movement Restoration After the Stroke. Kibernetika i vycislitel’naa tehnika. 2017. No 3 (189), pp. 61-78. (in Ukrainian)
https://doi.org/10.15407/kvt189.03.061

14. Belova A., Shchepetova O. Scales, tests and questionnaires in medical rehabilitation. Moscow: Antidor, 2002. 440 p. (in Russian)

15. Smychek V., Ponomareva E. Craniocerebral trauma (clinic, treatment, examination, rehabilitation). Minsk: Research Institute of ME and R, 2010. 430 p. (in Russian)

16. Vovk M.I., Kutsyak O.A. Information technology for forming a personal movement rehabilitation plan after a stroke. Cybernetics and Computer Engineering. 2020. No 3 (201). pp. 87-99.
https://doi.org/10.15407/kvt201.03.087

17. Vovk M.I., Kutsyak O.A. Mobile AI-technology for forming the personalized movements rehabilitation plan after a stroke. Cybernetics and Computer Engineering. 2021. No 4 (206). pp. 73-88.
https://doi.org/10.15407/kvt206.04.073

18. Vovk M.I., Kutsyak O.A. AI-technology of motor functions diagnostics after a stroke. Cybernetics and Computer Engineering. 2021. No 2 (204). pp. 84-100.
https://doi.org/10.15407/kvt204.02.084

Received 24.03.2022

Issue 1 (207), article 6

DOI:https://doi.org/10.15407/kvt207.01.074

Cybernetics and Computer Engineering, 2022, 1(207)

Kiforenko S.I., DSc (Biology), Senior Researcher
Leading Researcher of the Department of Application
Mathematical and Technical Methods in Biology and Medicine
ORCID: 0000-0001-2345-6789
e-mail: skifor@ukr.net

Belov V.M., DSc (Medicine), Professor,
Head of the Department of Application
Mathematical and Technical Methods in Biology and Medicine
ORCID: 0000-0001-8012-9717
e-mail: motj@ukr.net

Hontar T.M., PhD (Biology), Senior Researcher
Senior Researcher of the Department of Application
Mathematical and Technical Methods in Biology and Medicine
ORCID: 0000-0002-9239-0709
e-mail: gtm_kiev@ukr.net

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,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

THE HIERARCHY PRINCIPLE AS THE BASIS OF BIOLOGICAL SYSTEMS RESEARCH

Introduction. The article illustrates the feasibility of using the methodology of a systematic approach for the rational organization of research in solving biomedical problems at the stages of diagnosis, prognosis and correction of the condition. The effectiveness of using the principle of hierarchy as one of the main organizational principles of systems analysis is illustrated by specific examples of quantitative assessment of Health and its components and in the development of hierarchical modeling technology using mathematical models of varying complexity in a single technological cycle simultaneously.

The purpose of the paper is to show the expediency of using the principle of hierarchy on the examples of developing information-structural model of health category as an integrative structural concept and synthesis of hierarchical modeling technology as a basis for modern preclinical trials.

Results A hierarchical structure of health assessment technology has been developed, which includes conceptual level, management level: synthesis of assessment models and algorithms for calculating health reserves according to the norm index, level of synthesis of technological scaling procedures and diagnostic conclusions.

The technology of mathematical modeling using the hierarchy of models of different complexity for simulation research of different algorithms for glycemic control (analytical, numerical, simulation) to predict the glycemic profile at the stage of preclinical trials.

Conclusions. The hierarchical organization of the structure of the study of the category of health allowed to receive quantitative and verbal conclusions about the state of health reserves in general and all its components, taking into account the norm index, which increased the resolution of estimation algorithms. The proposed technology of hierarchical modeling of glycemic regulation in patients with diabetes allows to assess at the preclinical stage the peculiarities of the use of regulatory algorithms to prevent errors directly in the practice of treatment.

Keywords: the hierarchy principle, information-structural model of the health, hierarchical modeling, glycemic control system, simulation pre-clinical trials.

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16. Gritsenko V.I. Vovk M.I., Kotova A.B., Kiforenko S.I., Belov V.M. Information technologies in biology and medicine. Course of lectures. Kyiv: Naukova Dumka, 2007. 382p. (In Ukrainian)

17. Belov V.M., Kotova A.B. Human health: challenges, methods, approaches. Kyiv: Naukova Dumka, 2017. 132 p. (In Russian)

18. Kiforenko S.I., Kotova A.B. Multidimensionality as a basis for systematic health assessment. Kibernetika i vycislitel’naa tehnika. 2006. Issue. 150. S. 60-69. (In Russian)

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21. Aliev T.I. Research of complex systems based on a combined approach

http://simulation.su/uploads/files/default/immod-2003-1-50-55.pdf (In Russian)

22. Kiforenko S.I. Hierarchical modeling as the basis of the technology of preclinical testing of algorithms for the treatment of equal glycaemia. Kibernetika i vycislitel’naa tehnika. Iss.187, 2017. P. 80-96. (In Ukrainian)
https://doi.org/10.15407/kvt187.01.080

23. Dalla Man C., Micheletto F., Lv D., Breton M., Kovatchev B., Cobelli C. The UVA/PADOVA type 1 diabetes simulator: new features. J. Diabetes Sci. Technol. 2014; 8 (1): 26-34.
https://doi.org/10.1177/1932296813514502

Received 21.02.2022

Issue 1 (207), article 5

DOI:https://doi.org/10.15407/kvt207.01.059

Cybernetics and Computer Engineering, 2022, 1(207)

O.S. Kovalenko, DSc (Medicine), Professor,
 Head of the Medical Information Systems Department
ORCID 0000-0001-6635-0124
e-mail: askov49@gmail.com

L.M. Kozak, DSc (Biology), Senior Researcher,
Leading Researcher of the Medical Information Systems Department
ORCID: 0000-0002-7412-3041
e-mail: lmkozak52@gmail.com

M. Najafian Tumajani,
Junior Researcher of the Medical Information Systems Department,
ORCID:
e-mail: najafian@mail.ru

O.O. Romanyuk,
Junior Researcher of the Medical Information Systems Department
ORCID:0000-0002-6865-1403
e-mail: ksnksn7@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,
40, Glushkov ave., Kyiv, 03187, Ukraine

EXPERIENCE AND PROSPECTS OF CREATING MEDICAL INFORMATION SYSTEMS AND INFORMTION TECHNOLOGIES TO SUPPORT MEDICAL CARE

Introduction. One of the four flagship initiatives identified by the WHO as health priorities for the coming years is the Flagship Initiative to enable citizens for receive quality health care through digital health care. The use of digital medical technologies to provide health care will serve for strengthening the health care system, empowering patients and achieving the principle of “health for all”.

The purpose of the paper is to summarize the experience and latest results of the scientists of the Medical Information Systems Department of the International Center for Research and Development of Medical Information Systems and Information Technologies of Digital Medicine against the background of the general process of digital transformation in medicine.

Results. The main characteristics and principles of building modern medical information systems (MIS) as components of the digital medicine ecosystem are determined. Internal and external information flows of MIS are analyzed. To further differentiate the representative attributes of these documents, three similar but different technologies associated with the patient card were identified: electronic medical records, electronic health records and electronic patient health passport, each of which is differentiated based on the level of patient orientation. Based on one of the principles of “5Ps medicine”, the principle of personalization, the structure of personal medical storage is determined, which according to modern challenges is needed by all participants in digital medicine infrastructure (patients, doctors, laboratories and functional diagnostics departments, etc.). To ensure the interconnection of such repositories, models of business processes of accumulation and exchange of digital medical data have been created and based on them mobile applications, modules for accumulation and exchange of digital medical data between different users in the process of diagnostic data analysis have been developed. The interaction of mobile applications with the local information environment of the health care institution is analyzed and its features are taken into account in the created specialized mobile software modules of accumulation and analysis of personal medical data.

Conclusion. The developed model of digital transformation in medicine, which includes digital methods of obtaining and analyzing biomedical signals, digital medical images, methods of forming electronic medical records and documents, allowed to create methods and tools for building the digital medicine ecosystem using global intellectual resources to provide the necessary level for analysis Big Data and decision support for doctors at all stages of medical care. The use of developed mobile applications of accumulation, analysis and exchange of personal medical data allows to review the accumulated data, assess and predict human health according to the developed Data Mining models and implement medical data exchange of different origins between patient and doctor.

Keywords: medical information systems, digital medicine ecosystems, medical information technologies, mobile applications, classification models Data Mining.

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REFERENCES
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6. Kozak L.M., Kovalenko A.S., Kryvova O.A., Romanyuk O.A. Digital Transformation in Medicine: From Formalized Medical Documents to Information Technologies of Digital Medicine. Kibernetika i vycislitel’naa tehnika. 2018. 4(194). P. 61-78.
https://doi.org/10.15407/kvt194.04.061

7. The Digital Imperative. The imperative for a consumer-centric, digitally enabled health ecosystem. Delloite. 10 p.: https://www.kff.org/health-costs/poll-finding/data-note-americans-challenges-with-health-care-costs/

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13. Kovalenko A.S., Kozak L.M., Ostashko V.G. Telemedicine – development of a unified medical information space. Upravla!û!!ŝ!ie sistemy i ma!š!iny. 2005. No3. C. 86-92. (In Russian)

14. Kovalenko A.S., Kozak L.M., Romanyuk O.A. Information technology of digital medicine. Kibernetika i vycislitel’naa tehnika. 2017. No1(187). C.67-79. (In Russian)
https://doi.org/10.15407/kvt187.01.067

15. Romaniuk, O. O., Kozak, L. M., and Kovalenko, O. S. Formation of Interoperable Digital Medicine Information Environment: Personal Medical Data. Sci. innov. 2021. V. 17, no. 5. P. 50-62.

16. Kryvova O.A., Kozak L.M. Information Technology for Classification of Donosological and Pathological States Using the Ensemble of Data Mining Methods. Cybernetics and Computer Engineering. 2021, 1(203), pp 77-96.
https://doi.org/10.15407/kvt203.01.077

17. Officials Should Target 20 Key Areas to Transform Health Care System https://www8.nationalacademies.org/onpinews/newsitem.aspx?RecordID=10593

18. Nanotechnology is a key priority for the foreseeable future in medicine http:// www.nanolab.com.ua/publicacii/article4.html

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Received 14.01.2022

Issue 1 (207), article 4

DOI:https://doi.org/10.15407/kvt207.01.046

Cybernetics and Computer Engineering, 2022, 1(207)

L.S. Zhiteckii, PhD (Engineering),
Acting Head of the Department of
Intelligent Automatic Systems
e-mail: leonid_zhiteckii@i.ua

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,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

PROBLEMS AND PROSPECTS FOR THE INTELLECTUALIZATION OF AUTOMATIC CONTROL SYSTEMS

Introduction. The improvement of automatic control systems via their intellectualization is the important problem from both theoretical and practical points of view. The presence of adaptation and learning processes intrinsic to the natural intelligence makes it possible to consider the modern adaptive and learning systems as some intelligent control systems of the simplest type.

The purpose of this paper is to outline briefly the world-class results related to the efficient adaptive control and achieved in Intelligent Automatic Systems Department during the last 25 years and also to point out on problems of future research in this scientific area.

Results. A new adaptive control theory which has recently been completed represent the significant achievement to deal with the control systems in the presence of both parameter and nonparameter uncertainties. The main distinguishing feature of this theory is that it requires no information about the constrained membership set of unknown plant parameters and the bounds on arbitrary unmeasurable disturbances. Utilizing its methods, we can ensure the desired performance indices of the control systems with uncertain plants whereas the existing methods become quite unacceptable in the same situation.

Conclusion. Based on recent results concerning the adaptation and learning problems, we propose to take a next step toward to novel intelligent automatic control systems containing complex nonlinear plants. However, new perspective methods guaranteeing a perfect behavior of the closed-loop control systems, in particular, the stability of these control systems should be devised before implementing them in practical applications. This as yet unsolved scientific problem remains the subject of future theoretical research.

Keywords: adaptive and learning control system, automatic intelligent control system, parameter and nonparameter uncertainties, unmeasured disturbance, complex nonlinear plant. 

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Received 21.03.2022