Issue 3 (205), article 1

DOI:https://10.15407/kvt205.03.005

Cybernetics and Computer Engineering, 2021, 3(205)

GRITSENKO V.I.1, Corresponding Member of NAS of Ukraine,
Director of 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
ORCID: 0000-0003-4813-6153
e-mail: vig@irtc.org.ua

GLADUN A.Ya.1, PhD (Engineering),
Senior Researcher of the Department of Complex Research of Information Technologies and Systems
ORCID: 0000-0002-4133-8169
e-mail: glanat@yahoo.com

KHALA K.O.1,
Researcher of the Department of Complex Research of Information Technologies and Systems
ORCID: 0000-0002-9477-970X
e-mail: cecerongreat@ukr.net

Martínez-Béjar R.2, PhD (Informatics),
Professof at the Department of Information and Communication Engineering
ORCID: 0000-0002-9677-7396
e-mail: rodrigo@um.es

1 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

2 Department of Information and Communication Engineering and Artificial Intelligence University of Murcia CP 30180 Bullas, Spain

SEMANTICAL SIMILARITY EVALUATION METHOD OF CONCEPTS FOR COMPARISON OF ONTOLOGIES IN APPLIED PROBLEMS OF ARTIFICIAL INTELLIGENCE

Introduction. The expediency of reapplication of ontology in applied intelligent information systems (IIS), which are focused on functioning in the open Web environment on the basis of Semantic Web technologies, is substantiated in the work. Features of ontology storage and management platforms and their metadata are analyzed. Possibilities of searching in ontology repositories and their reuse in IIS are considered. The mechanisms of ontology search based on semantic processing of their metadata, analysis of ontology structure using metrics of semantic similarity between their concepts related to the current user task are presented.

The purpose of the article is the development of algorithms and methods for evaluating semantic models, which consist in combining qualitative (ontological) representation of knowledge with quantitative (numerical) evaluation of ontologies and their parameters (semantic proximity, semantic distance, semantic affinity) aimed at finding similarities different ontologies

Methods. Methods of ontological analysis of objects of the subject area, theoretical and multiple approaches to determine the degree of closeness of two objects by comparing their properties (feature matching) and traditional methods of statistical analysis are used to solve the tasks set in the work.

Results. The proposed method of estimating semantic similarity allows on the basis of semantic analysis of natural annotations of metadata both ontologies and data (including Big Data) to perform the task of their interpretation and selection to the problem to be solved by the applied IIS or application. The obtained results allow to create original IIS for artificial intelligence in economics, medicine, national security, defense and social sphere.

Conclusion. We proposed an original approach to the evaluation and analysis of metadata (ontologies, data), based on semantic analysis of metadata and determining the semantic similarity of structural data models (ontologies, data) and the formation of a ranked set of related ontologies to solve problems of artificial intelligence. The application of methods for defining semantically similar concepts is presented as a tool for semantic comparison of the structure of ontologies, which were found in the repository under formal conditions, with a poorly structured PM-description. At present, there is no generally accepted standard for presenting metadata, so the proposed methods of analysis of PM annotations are the most adequate means of comparing the semantics of ontologies, data with the problems for which they can be used.

Keywords: semantic similarity, formal ontology model, metadata, metadata standards, intelligent information system, ontology repository.

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Received 11.01.2021

Issue 3 (205)

DOI:https://doi.org/10.15407/kvt205.03

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TABLE OF CONTENTS:

Informatics and Information Technologies:

Gritsenko V.I., Gladun A.YA., Khala K.O., Rodrigo Martínez-Béjar
Semantical Similarity Evaluation Method of Concepts for Comparison of Ontologies in Applied Problems of Artificial Intelligence

Chabaniuk V.S., Kolimasov I.M.
Critical Systemic Properties of Electronic Atlases New Generation. Part 2: Research Results

Intelligent Control and Systems:

Aralova N.I., Klyuchko.M.V., Mashkin.I.V., Mashkina I.V., Radziejowski P.A., Radziejowska M.P.
Mathematical Model of Conflict-Controlled Processes in Self-Organization of Respiratory System

Medical and Biological Cybernetics:

Danilova V.A., Shlykov V.V., Dubko A.G.
Determination of Parameters of Influence of High Frequency Current on Living Tissues

Yermakova I.I., Bogatonkova A.I., Nikolaienko A.YU., Tadeeva Yu.P., Hrytsaiuk O.V., Solopchuk J.M.
M-Health Technology for the Forecast of the Human Condition in Extreme Environmental Conditions

Issue 2 (204), article 5

DOI:https://doi.org/10.15407/kvt204.02.084

Cybernetics and Computer Engineering, 2021, 2(204)

VOVK M.I., PhD (Biology), Senior Researcher,
Head of Bioelectrical Control & Medical Cybernetics Department
e-mail: vovk@irtc.org.ua; imvovk3940@gmail.com

KUTSIAK O.A., PhD (Engineering),
Senior Researcher of Bioelectrical Control & Medical Cybernetics Department
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. Glushkov av. Kyiv, 03187, Ukraine

AI-TECHNOLOGY OF MOTOR FUNCTIONS DIAGNOSTICS AFTER A STROKE

Introduction. Diagnostics of motor functions plays an important role in the motor functions restoration after stroke. Synthesis of effective technologies for personalized assessment of motor functions disorders at different rehabilitation stages is an urgent scientific and applied task.

The purpose of the paper is to develop information technology for diagnostics of motor functions deficit after stroke, that uses artificial intelligence tools to increase the effectiveness of the diagnostic process.

Results. The theoretical and practical foundations to synthesize AI-technology for personal diagnostics of motor functions deficit, and the assessment of their restoration as a result of rehabilitation measures after stroke have been developed. For informational assistance to the physician in the diagnostic process, artificial intelligence is used. A new class of mobile digital medicine tools – the specialized software modules for motor functions diagnostics “MovementTestStroke 1.1 (PC)” installed in the PC-structure, and “MovementTestStroke 1.1 (MD)” installed in mobile platforms running under Android operation system have been developed. Software implementation — Visual Studio 2019, C# programming language. Structural and functional models of user – software modules interaction, algorithms for motor function deficit diagnostics, and UML-diagrams of these modules are presented.

Functional features of the technology: an expanded range of evidence criteria for personalized quantitative assessment of limb movements deficit, storage in the Database and display on the interface the results of deficit assessment, as well as the deficit dynamics during the rehabilitation course in a convenient form (tables, graphs) make it possible to reduce the physician’s error, prevent complications, identify the disorders specifics, compare the rehabilitation effectiveness of the upper and lower limbs, their distal and proximal parts, including fine motor skills of the hand, restoration of which helps to restore speech in motor or motor and sensory aphasia.

Conclusions. The usage of artificial intelligence tools to diagnose motor deficit will increase the diagnostic effectiveness, and, as a consequence, rehabilitation services for patients after stroke.

Keywords: diagnostics, motor functions, stroke, personal quantitative assessment, criteria, technology, artificial intelligence, software module, structural-functional model, algorithm, activity diagram.

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REFERENCES

1. Norrving Bo. Action Plan for Stroke in Europe 2018-2030. European Stroke Journal. 2018. Vol. 3(4). pp. 309-336.
https://doi.org/10.1177/2396987318808719

2. 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. Cybernetics and Computer Engineering. 2017, No 3 (189), pp. 61-78. (in Ukrainian)
https://doi.org/10.15407/kvt189.03.061

3. Gritsenko V.I., Vovk M.I. Trenar – Innovative Technology of Restoration of Movements. Science and Business – the basis of economic development: materials of the International Scientific and Practical Forum. Ukraine, Dnipropetrovsk, 2012, pp. 204-206. (in Russian)

4. Varun H Buch, Irfan Ahmed, Mahiben Maruthappu. Artificial intelligence in medicine: current trends and future possibilities. Br J Gen Pract. 2018. No 68(668). pp. 143-144.
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5. 5. Bernard Marr. The 9 Biggest Technology Trends That Will Transform Medicine And Healthcare In 2020. URL: https://www.forbes.com/sites/bernardmarr/2019/11/01/the-9-biggest-technology-trends-that-will-transform-medicine-and-healthcare-in-2020/?sh= 6db7334072cd (Last accessed: 1.05.2021)

6. Ahuja A.S. The impact of artificial intelligence in medicine on the future role of the physician. PeerJ. 2019. URL: http://doi.org/10.7717/peerj.7702
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8. 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.
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9. Belova A., Shchepetova O. Scales, tests and questionnaires in medical rehabilitation. Moscow: Antidor, 2002. 440 p. (in Russian)

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

11. Certificate of registration the copyright “Computer program “Diagnostics of deficit of general limb movement, fine motor skills of the hand, walking form by the technique for quantitative assessment of movements deficit in patients after stroke “MovementTestStroke 1.0 (PC)””” / M.I. Vovk, O.A. Kutsiak (Ukraine); No. 98161; published dated 16.06.2020 [in Ukrainian].

12. Booch G., Rumbaugh J., Jacobson I. The Unified Modeling Language User Guide. Boston: Addison-Wesley Professional, 1998. 391 p.

13. Fowler M. UML Distilled: A Brief Guide to the Standard Object Modeling Language. Boston: Addison-Wesley Professional, 2004. 175 p.

Received 01.04.2021

Issue 2 (204), article 4

DOI:https://doi.org/10.15407/kvt204.02.064

Cybernetics and Computer Engineering, 2021, 2(204)

FAINZILBERG L.S.1, DSc. (Engineering), Professor,
Chief Researcher of the Department of Automatic Systems
ORCID: 0000-0002-3092-0794
e-mail: fainzilberg@gmail.com

SOLOVEY S.R.2, Student Faculty of Biomedical Engineering,
e-mail: maximum.lenovo.ml@gmail.com

1International 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. Glushkova av., Kyiv, 03187, Ukraine,

2The National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»
37, Peremohy av., Kyiv, 03056, Ukraine

SELF-LEARNING INFORMATION TECHNOLOGY FOR DETECTING RESPIRATORY DISORDERS IN HOME CONDITION

Introduction. In connection with the COVID-19 pandemic, it is important to start treatment promptly in case of a threat of developing viral pneumonia in a patient. The solution to this problem requires the creation of new means for detecting respiratory disorders with a minimum probability of “missing the target”. At the same time, it is equally important to minimize visits to medical institutions by healthy patients because of the danger of their contact with possible carriers of coronavirus infections, that is, to minimize the likelihood of a «false alarm».

Purpose of the article is to develop a method that allows a patient to signal at home about the advisability of contacting a medical institution for an in-depth examination of the respiratory system, and to assess the possibility of implementing this method on a smartphone using a built-in microphone.

Methods. A distinctive feature of the proposed approach lies in the construction of a personalized standard of normal respiratory respiration for a particular patient based on self-learning from a finite sample of observations at home and in comparison, based on original computational algorithms of phonospirograms of sound signals of the following observations with the standard.

Results. A prototype of information technology has been developed that will provide home alarms about possible respiratory disorders, requiring consultation with a doctor and the need for an in-depth medical examination.

It is shown that the construction of a personalized standard of normal breathing can be carried out based on the use of a set of original computational procedures for a finite sample of realizations, independently registered by the user using a microphone built into a smartphone. The algorithm for constructing a standard is based on digital processing of a matrix of paired distances between phonospirograms of the final training sample of observations.

Findings. A software application that provides the implementation of the proposed computational procedures can be implemented on a smartphone of average performance running the Android operating system.

Keywords: respiratory noises, intelligent IT, computational procedures, smartphone.

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Received 02.03.2021

Issue 2 (204), article 3

DOI:https://doi.org/10.15407/kvt204.02.049

Cybernetics and Computer Engineering, 2021, 2(204)

SHEPETUKHA Y.M., PhD (Engineering), Senior Researcher,
Leading Researcher of the Intelligent Control Department
ORCID: 0000-0002-6256-5248
e-mail: yshep@meta.ua

VOLKOV  O.Ye.,
Head of the Intelligent Control Department
ORCID: 0000-0002-5418-6723
email: alexvolk@ukr.net

KOMAR M.M.,
Senior Researcher of Intelligent Control Department
ORCID: 0000-0002-0119-0964
e-mail: nickkomar08@gmail.com

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

INTELLECTUALIZATION OF DECISION MAKING PROCESSES IN AUTONOMOUS CONTROL SYSTEMS

Introduction. Scientific-technical level of any country in a modern world is mainly determined by a current state and development rate of informational technologies. At the same time, the main avenue of information technologies’ improvement is their intellectualization. Due to intellectualization, it became possible to create advanced systems with principally novel functional capabilities, in particular, high-speed computer systems able to autonomous actions in a complex and dynamic environment. Control means for complex objects and processes play an important role in the operation of autonomous systems. Therefore, the study of theoretical as well as applied issues of such systems’ construction is an important scientific and engineering problem.

The purpose of the paper is to examine both current state and development prospects of a new direction in the area of intelligent information technologies – the elaboration of autonomous control systems for complex objects and processes in a dynamic environment; to formulate a well-grounded approach for the increase in intellectualization level of decision processes in such systems.

Methods. The development of autonomous control systems, as well as the increase in decision making processes’ intellectualization level in such systems, is based on the usage of the following conceptual, theoretical and methodological instruments: the theory of informational technologies’ intellectualization, the methodology of intelligent control, the theoretical fundamentals of artificial intelligence systems’ construction, decision making methods, the methodology of image-based reasoning, methods for simulation of image-based comprehension of environment.

Results. An approach for the consistent usage of methods of artificial intelligence, decision making and intelligent control aimed at the development of autonomous means for the control of complex objects and processes has been examined. Appropriateness of creation of the systems profiled for operations in designated problem domains has been grounded. Both specific features and components of the framework for decision making in intelligent control systems have been determined. Both necessity of the creation of intelligent environment and important role of sensor networks have been stressed. Methodology for the construction of informational images, which represent the most important components of a current situation, has been proposed. Examples of the usage of informational images for performing both dynamic and evolutional re-planning have been considered.

Conclusions. A reasonable way for the development of intelligent control systems is the one that provides a consistent usage of different types of models. Image-based representation of a current situation’s essential interconnections is an efficient instrument for the intellectualization at different stages of decision making processes – alternative generation, understanding of inconsistencies among different data sources, execution of choice procedure, evaluation of results. The application of artificial intelligence elements for decision making in autonomous systems is especially well-grounded in cases of time shortage as well as availability of a great number of existing alternatives.

Keywords: intellectualization of information technologies, intelligent control, decision making, autonomy, artificial intelligence, image, uncertainty, adaptation.

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Received 04.04.2021

Issue 2 (204), article 2

DOI:https://doi.org/10.15407/kvt204.02.020

Cybernetics and Computer Engineering, 2021, 2(204)

CHABANIUK V.S.1,2, PhD (Phys.-Math.),
Senior Researcher of the Cartography Department, Institute of Geography,
Director of “Intelligence systems-GEO” LLC,
ORCID: 0000-0002-4731-7895
email: chab3@i.ua, chab@isgeo.kiev.ua

KOLIMASOV I.M.2,
Head of Production of “Intelligence systems-GEO” LLC,
ORCID: 0000-0002-4927-4200
email: kolimasov@ukr.net

KRAKOVSKYI S.P.1,
Junior Researcher of the Cartography Department, Institute of Geography,
ORCID: 0000-0001-5164-6272
email: krakovsp@gmail.com

1Institute of Geography, National Academy of Sciences of Ukraine
44, Volodymyrska str., 01054, Kyiv, Ukraine

2“Intelligence systems-GEO” LLC,
6/44, Mykilsko-Slobidska str., 02002, Kyiv, Ukraine

CRITICAL SYSTEMIC PROPERTIES OF ELECTRONIC ATLASES OF NEW GENERATION. PART 1: PROBLEM AND RESEARCH METHODS

Introduction. The revolutionary changes in information technology of the last two decades allow the construction of electronic atlases (EA), the capabilities of which are fundamentally richer than the capabilities of “classic” EA. This is achieved through the use of the systemic properties of the new generation of EA, which are therefore named systemic. Systemic EA remain the simplest and most effective spatial information models of territorial systems allowing applying them for the decision of many practical problems.

The purpose of the paper is to formulate the need for systemic EA and describe methods for studying their systemic properties. These methods will be used to find and describe critical systemic properties without which EA cannot be systemic.The methods are founded on Relational Cartography and Model-Based Engineering.

Results. The evolution of “classic” EA is considered: from paper atlases and their images to analytical atlases. It is shown that on the imaginary border of classic and nonclassic EA there are already new generation EA — systemic EA. Both the theory and practice of such systemic EA have many unresolved problems. Some of them are described in the article. The authors believe that many problems can be solved by implementing the critical systemic properties of EA. Two methods are used to study the problems and to prove the results: Conceptual frameworks and Solutions frameworks. Both the methods themselves and the possibility of their application to find the critical systemic properties of the new generation of EA are described.

Conclusions. The main problems of electronic atlases of the new generation are described and their solution is offered by a method of Conceptual frameworks and a method of Solutions framework.

Keywords: systemic electronic atlas, Conceptual framework, Solutions framework, critical system property.

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Received 22.03.2021

Issue 2 (204), article 1

DOI:https://doi.org/10.15407/kvt204.02.005

Cybernetics and Computer Engineering, 2021, 2(204)

GRITSENKO V.I., Corresponding Member of NAS of Ukraine,
Director of 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
ORCID: 0000-0003-4813-6153
e-mail:  vig@irtc.org.ua 

BABAK O.V., PhD (Engineering), Senior Researcher,
Ecological Digital Systems Department
ORCID: 0000-0002-7451-3314
e-mail: dep175@irtc.org.ua

SUROVTSEV I.V., DSc (Engineering), Senior Researcher,
Head of the Ecological Digital Systems Department
ORCID: 0000-0003-1133-6207
e-mail: dep175@irtc.org.ua, igorsur52@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, Acad. Glushkov av., Kyiv, 03187, Ukraine

PECULIARITIES OF INTERCONNECTION 5G, 6G NETWORKS WITH BIG DATA, INTERNET OF THINGS AND ARTIFICIAL INTELLIGENCE

Introduction. The 5G, 6G mobile technologies, which are actively developing in the world, and the Internet of Things (IoT), Big Data (BD), artificial intelligence (AI) are closely intertwined. It is important to understand the features of the relationship to effectively use them in new intelligent information technologies.

The purpose of the article is to highlight the most important features of the relationship, which are viewed on the basis of experience in implementing 5G and 6G technologies.

Results. the Internet of Things, industrial (IIoT), the Internet in total (IoE) use 5G, 6G technologies, as well as cloud, fog and boundary computing for high-speed communication with devices. Machine learning (ML), Date Mining, neural networks and simulation are used to analyze BD. AI algorithms are an integral part of all technologies, they allow you to intelligently connect and control 5G / 6G + IoT + BD + AI.

Conclusions. 5G and 6G high-speed networks, Internet of Things technology, cloud computing, big data analysis and artificial intelligence are necessary conditions for the further development of the digital economy.

Keywords: communication networks, big data, Internet of Things, artificial intelligence.

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Received 20.03.2021

Issue 2 (204)

DOI:https://doi.org/10.15407/kvt204.02

Download Issue 2 (204) as PDF
View web version

TABLE OF CONTENTS:

Informatics and Information Technologies:

Gritsenko V.I., Babak O.V., Surovtsev I.V.
Peculiarities of Interconnection 5G, 6G Networks with Big Data, Internet of Things and Artificial Intelligence

Chabaniuk V.S., Kolimasov I.M., Krakovskyi S.P.
Critical Systemic Properties of Electronic Atlases of New Generation. Part 1: Problem and Research Methods

Intelligent Control and Systems:

Shepetukha Yu.M., Volkov O.Ye., Komar M.M.
Intellectualization of Decision Making Processes in Autonomous Control Systems

Medical and Biological Cybernetics:

Fainzilberg L.S., Solovey S.R.
Self-learning Information Technology for Detecting Respiratory Disorders in Home Conditions

Vovk М.І., Kutsiak О.А.
AI-Technology of Motor Functions Diagnostics after a Stroke

Issue 1 (203), article 5

DOI:https://doi.org/10.15407/kvt203.01.077

Cybernetics and Computer Engineering, 2021, 1(203)

KRYVOVA O.A.,
Researcher, the Medical Information Systems Department
e-mail: ol.kryvova@gmail.com
ORCID: 0000-0002-4407-5990

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

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

INFORMATION TECHNOLOGY FOR CLASSIFICATION OF DONOSOLOGICAL AND PATHOLOGICAL STATES USING THE ENSEMBLE OF DATA MINING METHODS

Introduction. The digital technologies implementation provides registration of large amounts of bio-medical data (ECG, EEG, electronic medical records) as a basis for assessing and predicting the patients` condition. Data Mining methods allow to identify the most informative indicators and typological groups, to classify the person` functional state and the patients` disease stages to predict their changes.

The purpose of the paper is to develop information technology for the classification of human health states using a set of Data Mining methods and to carry out its validation on examples of an operators` functional state and patient’s disease severity.

Results. The developed IT unites several stages: I — data pre-processing; II — clustering, selecting the homogeneous groups (data segmentation); III — predictors` identification; IV — classifying the studied states, development of predictive models using machine learning algorithms (Decision trees, Support vector machines, neural networks) and the method cross-validation. The proposed IT was used to classify the operators` functional statе and the patients` severity in case of disease progression.

Conclusions. The IT use to assess the operators` activity successes made it possible to identify the most informative HRV indicators, changes in which can predict the operators` reliability, taking into account the type of vegetative regulation. Assessing the disease activity of children with dysplasia with IT use made it possible to identify diagnostic markers of CCC and develop diagnostic rules for determining the stages of the disease by ECG parameters (T wave symmetry, an integral indicator of the ST_T segment shape).

Keywords: information technology, Data Mining, machine learning models, severity of the patient.

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Received 31.11.2020

Issue 1 (203), article 4

DOI:https://doi.org/10.15407/kvt203.01.060

Cybernetics and Computer Engineering, 2021, 1(203)

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

KLYUCHKO O.M.2, PhD (Biology), Associate Professor,
Associate Professor, Faculty of Air Navigation,
ORCID: 0000-0003-4982 7490
e-mail: kelenaXX@nau.edu.ua

MASHKIN V.I.1, PhD (Engineering), Senior Researcher,
Senior Researcher of Optimization of Controlled Processes Department,
ORCID: 0000-0002-4479-6498,
e-mail: mashkin_v@ukr.net

MASHKINA I.V.3, PhD (Engineering), Associate Professor
Associate Professor, Faculty of Information Technology and Management
ORCID: 0000-0002-0667-5749,
e-mail: mashkina@kubg.edu.ua

1V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine.
40, Acad.Glushkov av., Kyiv, 03680, Ukraine
2Electronics and Telecommunications National Aviation University,
1, Lubomyr Huzar av., Kyiv, 03058, Ukraine
3Borys Grinchenko Kyiv University,
18/2, Bulvarno-Kudriavska str., Kyiv, 04053 Ukraine, 04053

MATHEMATICAL MODEL OF FUNCTIONAL RESPIRATORY SYSTEM FOR THE INVESTIGATION OF HARMFUL ORGANIC COMPOUNDS INFLUENCES IN INDUSTRIAL REGIONS

Introduction. The areas around industrial objects, and now in regions of military actions are characterized by a high content of pollutants. Qualitative spectrum of these pollutants is extremely broad and contains both inorganic and organic elements and compounds. In particular, environmental pollution is caused by hydrocarbons with wide range of chemical structures, the study of which is very important due to their harmful and toxic influences on living organisms. The methods, currently used in medicine, give only a “thin slice” of current pathological state of organism, but they cannot predict the long-term consequences of such lesions. That is why it seems appropriate to use mathematical models that simulate the movement of organic compounds in the respiratory and circulatory systems and thus to predict possible pathologies in organs and tissues caused by hypoxic states that occur when these organs and tissues are affected.

Purpose of the paper is to create a mathematical model of functional respiratory system, which simulates the influence of external environment on the parameters of self-organization of human respiratory system in the dynamics of respiratory cycle; and thus to predict hypoxic conditions during tissue damage by hydrocarbons.

Results. The mathematical model for respiratory gases transport and mass transfer in human organism is represented as a system of differential equations, which is a controlled dynamic system, and the states of which are determined by oxygen and carbon dioxide stresses in each structural link of the respiratory system (alveoli, blood, and tissues) at each moment of time. The model is supplemented by the equations of transport of the substances in each structural link as well as by the mathematical model of organism oxygen regimes regulation. The model includes seven groups of tissues – brain, heart, liver and gastrointestinal tissues, kidneys, muscle tissue etc. The algorithm of the work and iterative procedure of research with application of suggested complex are given.

Conclusion. The proposed mathematical model for studying of the transport of organic substances in human organism which consists of differential equations of respiratory gases transport and mass transfer in it, and for the transport of organic compounds is theoretical only for today. However, in the presence of appropriate array of experimental data, it will be able to monitor the state of functional respiratory system after the pathogenic organic compounds inquiry, which may be useful in choosing of strategies and tactics for the treatment of particular lesion.

Keywords: functional respiratory system, regulation of organism oxygen regimes, harmful organic substances, hypoxic state, mathematical model of respiratory system, transport of gases by blood, self-regulation of respiratory system.

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Received 04.11.2020