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Issue 2 (188), article 1

DOI:https://doi.org/10.15407/kvt188.02.005

Kibern. vyčisl. teh., 2017, Issue 2 (188), pp.

Grytsenko V.I., Corresponding Member of NAS of Ukraine, Director
e-mail: vig@irtc.org.ua
International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and of Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine

Rachkovskij D.A., Doctor of Engineering, Leading Researcher,
Dept. of Neural Information Processing Technologies,
e-mail: dar@infrm.kiev.ua
International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and of Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine

Frolov A.A., Doctor of Biology, Professor,
Faculty of Electrical Engineering and Computer Science FEI,
e-mail: docfact@gmail.com
Technical University of Ostrava, 17 listopadu 15, 708 33 Ostrava-Poruba, Czech Republic

Gayler R., PhD,
Independent Researcher,
r.gayler@gmail.com
Melbourne, VIC, Australia

Kleyko D., PhD post graduated,
Department of Computer Science, Electrical and Space Engineering,
denis.kleyko@ltu.se
Lulea University of Technology, 971 87 Lulea, Sweden

Osipov E., PhD, Professor,
Department of Computer Science, Electrical and Space Engineering,
evgeny.osipov@ltu.se
Lulea University of Technology, 971 87 Lulea, Sweden

NEURAL DISTRIBUTED AUTOASSOCIATIVE MEMORIES: A SURVEY.

Introduction. Neural network models of autoassociative, distributed memory allow storage and retrieval of many items (vectors) where the number of stored items can exceed the vector dimension (the number of neurons in the network). This opens the possibility of a sublinear time search (in the number of stored items) for approximate nearest neighbors among vectors of high dimension.

The purpose of the paper is to review models of autoassociative, distributed memory that can be naturally implemented by neural networks (mainly with local learning rules and iterative dynamics based on information locally available to neurons).

Scope. The survey is focused mainly on the networks of Hopfield, Willshaw, and Potts, that have connections between pairs of neurons and operate on sparse binary vectors. We discuss not only autoassociative memory, but also the generalization properties of these networks. We also consider neural networks with higher-order connections, and networks with a bipartite graph structure for non-binary data with linear constraints.

Conclusions. In conclusion we discuss the relations to similarity search, advantages and drawbacks of these techniques, and topics for further research. An interesting and still not completely resolved question is whether neural autoassociative memories can search for approximate nearest neighbors faster than other index structures for similarity search, in particular for the case of very high dimensional vectors.

Keywords: distributed associative memory, sparse binary vector, Hopfield network, Willshaw memory, Potts model, nearest neighbor, similarity search

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131 Rachkovskij D.A. Binary vectors for fast distance and similarity estimation. Cybernetics and Systems Analysis. 2017. Vol. 53, N 1. P. 138–156. https://doi.org/10.1007/s10559-017-9914-x

132 Rachkovskij D.A. Distance-based index structures for fast similarity search. Cybernetics and Systems Analysis. 2017. Vol. 53, N 4. https://doi.org/10.1007/s10559-017-9966-y

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Recieved 15.04.2017

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ISSUE 2 (188)

DOI:https://doi.org/10.15407/kvt188.02

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TABLE OF CONTENTS:

Informatics and Information Technologies:

Grytsenko V.I., Rachkovskij D.A., Frolov A.A., Gayler R., Kleyko D., Osipov E.
Neural Autoassociative Memories for Binary Vectors: A Survey

Khorozov O.A.
Application of Fuzzy Logic for Telemedicine Systems

Intellectual Control and Systems:

Aralova N.I.
Reserch the Role of Hypoxia, Hypercaphnia and Hypometabolism in the Regulation of the Respiratory System in Their Internal and External Disturbances Based on the Mathematical Model

Medical and Biological Cybernetics:

Grygoryan R.D., Aksenova T.V., Degoda A.G.
A Computer Simulator of Mechanisms Providing Energy Balance in Human Cells

Rudenko А.V., Nastenko I.А., Zhurba O.А., Nosovets О.K., Shardukova Y.V., Lasoryshinets V.V.
Evaluation of Risk Factors for Operations Coronary Bypass Surgery on a Beating Heart

Information:

80TH Anniversary of Corresponding Member of NAS of Ukraine Vladimir Ilyich Gritsenko

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Issue 1 (187), article 6

DOI: https://doi.org/10.15407/kvt187.01.080

Kibern. vyčisl. teh., 2017, Issue 1 (187), pp.80-96

Kiforenko S.I., leading researcher at the Department of mathematical and technical methods in biology and medicine
e-mail: skifor@ukr.net

International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine

HIERARCHICAL MODELING — THE BASIS OF TECHNOLOGY OF PRECLINICAL TESTING OF GLYCEMIC LEVEL CONTROL ALGORITHMS

Introduction. In recent years there have been fundamental changes in the understanding of the requirements for the possibilities of using mathematical models. Now the model can not be seen as a self-contained object of research but as well as an element of integrated formulation of task management. Thereby it becomes information technology tool to solve this problem. It is possible to use the simulation results not only to solve control problems, but also for wider use — in the development of information systems support decision making in medical treatment and diagnostic process.

The purpose of the article is to summarize the experience in the development of hierarchical modeling technology of the system regulation of blood glucose using models different levels of complexity in a single technological cycle.

Methods. Structural and functional modeling, hierarchical modeling, methods of synthesis of mathematical models, methods for parameter identification and verification of models, methods of control theory.

Results. On the example of the regulation of blood glucose system is developed hierarchical modeling technology, based on the simultaneous use in a single technological cycle mathematical models of various levels of complexity: MAX, MIDI, MINI. The first type — a high level of complexity of the model — MAX-model — the closest to the modern ideas about the laws regulating the functioning of the system — used to simulate the object of research. The second type — these are more simple models of research object — MIDI model, — are used for the synthesis of control actions and fulfil the prediction function. The third type — the models are still at a lower level of complexity. — MINI model. Differential equations of these models have the analytical solutions and therefore it can possibly to calculate the control actions and functions of the forecast for calculation formulas.

Conclusions. This arrangement extends the range of simulation tasks and allows to analyze, at the stages of theoretical research and pre-clinical testing, the various aspects of the synthesis and test the effectiveness of the control algorithms that are relevant in diabetology.

Keywords: hierarchical simulation, system regulation of blood glucose, control algorithms, preclinical testing.

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REFERENCE

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3 Cobelli C., C. Dalla Man, G. Sparacino et al. Diabetes: models, signals, and control. IEEE reviews in biomedical engineering. 2009. No. 2. P. 54–96.
https://doi.org/10.1109/RBME.2009.2036073

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5 Nefedov V.P., Jasaitis A.A., Novoseltsev V.N. et al. Homeostasis at different levels of biological systems organization et al. Novosibirsk: Nauka, 1991. 232 p. (In Russian)

6 Drishel G. Regulation of blood sugar level. Regulatory processes in biology. M.: Nauka, 1960. P. 63–85 (In Russian).

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13 Biekomeditsina. Single Information Space / Ed. V.I. Gritsenko. Kiev: Nauk. Dumka, 2001. 318 p. (In Russian).

14 Antomonov Y.G., Kiforenko S.I., Mikulskaya I.A., Parokonnaya N.K. The mathematical theory of blood glucose system. Kiev: Nauk. Dumka, 1971. 82 p. (In Russian)

15 State and prospects of development of science in Ukraine (group of authors). Kiev: Nauk.dumka, 2010. 1008 p. (In Russian)

16 Antomonov Yu., S. Kiforenko, B. Allamiarov et al. Theoretical investigation of carbohydrate and lipometabolism systems and use of simplified mathematical models for control. Kybernetes. 1977. Vol.6. No 4. P. 297–303.
https://doi.org/10.1108/eb005463

17 Allamiyarov B.U., Kiforenko S.I. Experimental study and mathematical modeling of some indicators of carbohydrate and fat-lipid metabolism dynamics in a single injection of adrenaline. Mathematical models in biology. Kiev: Inst. of Cybernetics, 1974. P. 17–24 (In Russian).

18 Allamiyarov BU, Khamdamov R. Identification of the mathematical model of the level of glucose and blood free fatty acids control in diabetes. Proc. of the Academy of Sciences of the Uzbek SSR, Ser. tehn. Science, 1982. No 4. P. 38–43 (In Russian).

19 Cobelli, C. Federspil, G. Pacini et al. An integrated mathematical model of the dynamics of blood glucose and its hormonal control. Math. Biosci. 1981. Vol. 5. P.27–60.

20 Dartau L.A., Orkina E.L., Novoseltsev V.N., Sklyanik A.L. Carbohydrate metabolism: Integral models. Engineering physiology and modeling of the body’s systems. Novosibirsk: Nauka, 1987. P. 54–69 (In Russian)

21 Albisser A.M., Y Y. Amasaki, O.Broekhuyse, I. Tiran. Hypercomplex models of insulin and glucose dynamics: do they predict experimental results. Ann. Biomed. Engin. 1980. Vol. 8. P.539–557.
https://doi.org/10.1007/BF02363452

22 Cobelli C., E. Ruggari. Evaluation of portal/periphersi route and of algoritme for insulin delivery in the closed-loop control of glucose in diabetes. A modeling etudy. IEES Tranzasct. Biomed. Eng. 1983. Vol. 30. P. 93–103.
https://doi.org/10.1109/TBME.1983.325203

23 Cobelli C., A. Mari. Control of diabetes with artificial systeme for insulin delivery algorithm independent limitations revealed by a modeling study. IEEE Transact. Biomed. Eng. 1985. Vol. 32. P. 840–845.
https://doi.org/10.1109/TBME.1985.325499

24 Cobelli C. Modelling and identifications of endocrine-metabolic systems. Theoretical aspects and their importance in practice. Math. Biosci. 1984. Vol. 72. No 2. P. 263–289.
https://doi.org/10.1016/0025-5564(84)90113-5

25 Lapta S.I., S.S. Lapta. Functionally-phenomenological model of oral glucose-tolerance test. Problems of bionics. 2000. No 52. P. 52–57 (In Russian).

26 Lapta S.S., L.A. Pospelov, O.I. Solovyov. Computer early diagnosis of diabetes by methods of mathematical modelling. Vestn. NTU “KhPI”. 2014. No36 (1079). P. 55–61 (In Russian).

27 E.I. Sokol, S.S. Lapta. Mathematical model of carbohydrate metabolism regulation Vestn. NTU “KhPI”. 2015. No33 (1142). P. 152–157 (In Russian).

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Issue 1 (187), article 5

DOI: https://doi.org/10.15407/kvt187.01.067

Kibern. vyčisl. teh., 2017, Issue 1 (187), pp.67-80

Kovalenko A.S., Dr Medicine, Prof., Head of Department of Medical Information Systems
e-mail: askov49@gmail.com
Kozak L.M., Dr Biology, Leading Researcher of Department of Medical Information Systems
e-mail: lmkozak52@gmail.com
Romanyuk O.A., Junior Researcher of Department of Medical Information Systems
e-mail: ksnksn7@gmail.com

International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine

INFORMATION TECHNOLOGY FOR DIGITAL MEDICINE

Introduction. The need of health care institutions in the repeated use of digital medical images by different specialists during patient care and long-term storage for the analysis of diagnostic information determines the relevance of this work. The need for means and methods of storage of digital medical data with their subsequent processing and analysis, as well as on mobile devices for the collection, digital data processing and exchange increase.

The purpose of the article is to analyze the experience of creating medical information systems, the development of information technology support the storage and processing of digital medical information and the further development of information technology for digital medicine.

Results. Employees of the department of medical information systems for more than 20 years of activities of the International Research and Training Centre for Information Technologies and Systems NAS and MES of Ukraine solved the problem of constructing the medical information systems and information diagnostics technologies with the use of electronic medical records, methods and means of the mathematical analysis of medical data. The developed technology support for storing and processing digital medical information combines into a single functional network the medical information system, instrumental diagnostic systems and a system of conservation and archiving digital medical images. PACS and cloud technologies was used for long-term storage of digital medical images.

Conclusion. Organization of long-term storage of digital medical images obtained from the diagnostic systems in health care facilities, and the ability to use this information by doctors at their workplace in the current diagnostic and treatment process was provided by using the developed information technology support for storing and processing digital medical information.

Keywords: medical information system, information technology, digital medical imaging, long-term storage.

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Issue 1 (187), article 4

DOI: https://doi.org/10.15407/kvt187.01.049

Kibern. vyčisl. teh., 2017, Issue 1 (187), pp.49-67

Vovk M.I., PhD (Biology), Senior Researcher, Head of Bioelectrical Control & Medical Cy-bernetics Department
e-mail: dep140@irtc.org.ua

International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine

BIOENGINEERING SYSTEMS FOR HUMAN MOTOR FUNCTIONS CONTROL

Introduction. Movement training is one of the main factors to mobilize person’s reserves for movement restoration

The purpose of the article is to present the results of theoretical and applied researches focused on synthesis of information technologies for human motion control based on bioengineering systems as external control circuits.

Results. The evolution of bioengineering systems for motor control — multichannel electronic devices “Mioton-2”, “Mioton-3M”, “Mioton-604”, “Miokor”, adaptive device “Miostimul” and a new class of portable electronic devices of digital medicine for personal, biologically adequate, motor control “TRENAR®” are considered. Special EMG — signals processing and its transformation into informative visual and sound signals, that describe muscle contractions are used to develop different programms for muscle control. These programs based on different methods of muscle electrical stimulation and biofeedback are aimed on activaton of additional brain reserves to restore motor functions. New method and technology to restore motor speech, based on original technique of fine motor hand training by the technology “Trenar” is described. The results of clinical testing confirmed its effectiveness in motor speech restoration after the stroke.

Conclusion. The main benefits of the technology “Trenar” that leads to the increasing in efficiency of motor and speech rehabilitation are as follows: advanced range of training programs, based on different methods, original techniques of fine motor hand training allows one to select individual approach to rehabilitation process.

Keywords: bioengineering systems, electronic devices, bioelectric control, muscle stimulation, biofeedback, electromyographic signal, rehabilitation, movement, speech, personal approach.

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  1. Inventor’s certificate 190525 USSR. The method of motor control / L. Aleev, S. Bunimovich. No 1019769/31-16; claimed 26.06.65; published 29.02.67, Bull. No 2. (in Russian).
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  3. Inventor’s certificate 321 245 USSR. The method of motor control of a person /
    L. Aleev, S. Bunimovich, M. Vovk, V. Gorbanev, A. Shevchenko. No1455753/31-16; claimed 22.06.1970; registered 03.09.1971. (in Russian).
  4. Aleev L.S., Vovk M.I., Gorbanev V., Shevchenko A. «Mioton» in motor control. Kiev: Nauk. dumka, 1980. 142 p. (in Russian).
  5. Judin A.V., Shikova T.N. Miotonoterapiya in treatment of neuropathies. City Clinical Hospital №1 Togliatti. URL: http://www.f-med.ru/scient/nt_mitonoterapia.php (in Russian) (date of the application:11.11.16).
  6. Inventor’s certificate 929 054 USSR. Multichannel device for adaptive bioelectrical motor control of a person / L. Aleev, M. Vovk, V. Goranev, A. Shevchenko.
    No 2428608/28-13; claimed 13.12.76; published 23.05.82, Bull. № 19 (in Russian).
  7. Inventor’s certificate 976 952 USSR Multichannel device for adaptive bioelectrical motor control of a person / L. Aleev, M. Vovk, V. Goranev, A. Shevchenko.
    No 2436412/28-13; claimed 03.01.77; published 30.11.82, Bull. №44. (in Russian).
  8. Bioelectrically controlled electric stimulator of human muscles: United States Patent 4,165,750 Aug. 28, 1979.
  9. Elektrischer Anreger fur Menschenmuskeln mit bioelektrisher Steuerung: Deutshes Patentamt DE 2 811 463. 14.03.85 (in German).
  10. Vovk M.I., Kiforenko S.I., Kotova A. Biological and Biotechnical Systems as Purposeful Ones. Systems and Machines for Control. 2005. No 3. P.16–24 (in Russian).
  11. Gritsenko V.I., Kotova A., Vovk M et.al. Information technology in Biology and Medicine. Lecture course. K.: Nauk. Dumka, 2007. 382 p. (in Ukrainian).
  12. Vovk M.I. Bioinformatic technology of motor control of a person. Kibernetika i vyčislitelnaâ tehnika.. 2010. Iss. 161. P. 42–52 (in Russian).
  13. “Trenar” — innovative technology for motor restoration. Materials of the International scientific — practical forum «The Science and Business — a basis of development of economy». Dnepropetrovsk, 2012. P. 204–206 (in Russian).
  14. Vovk M.I. Bioinformatic technology of motor control as the direction of biological and medical cybernetics. Kibernetika i vyčislitelnaâ tehnika. 2013. № 174. P. 56–70 (in Russian).
  15. Vovk M.I. New opportunities for movement and speech rehabilitation. Kibernetika i vyčislitelnaâ tehnika. 2016. Iss.186. P. 78–93 (in Russian).
  16. Anohin P.K. The Sketches on Physiology of Functional Systems. Moscow: Medicine, 1975. 447 p. (in Russian).
  17. The method of Motor Control of a Person: pat. 41 795, Ukraine: IPC А61 N 1/36. No u 200814822; claimed 23.12.08; published 10.06.09, Bull. No 11. (in Ukrainian).
  18. Electrical stimulator: patent 32376, Ukraine: IPC А61 N 1/36. No u 2008 00632; claimed 18.01.08; published 12.05.08, Bull. No 9. (in Ukrainian).
  19. The Device for Electrical Stimulation with Biocontrol TRENAR-01. The Technique for Using / M. Vovk, V. Gorbanev, A. Shevchenko // The Inventor’s Certificate on author’s product right № 26 836, Ukraine — 09.12.2008 (in Ukrainian).
  20. The Device for Electrical Stimulation with Biofeedback TRENAR-02. The Technique for Using / M. Vovk, V. Gorbanev, A. Shevchenko // The Inventor’s Certificate on author’s product right № 37243, Ukraine. 04.03.2011 (in Ukrainian).
  21. Koltsova М.М. Motor activity and development of the child’s brain functions. М.: “Pedagogika”, 1973. 143 p. (in Russian).
  22. The way to treat speech desorders: pat. UA 111388, IPC A61N 1/36. No а 2014 06 092; claimed 03.06.2014, published 25.04.2016, Bull. No 18. (in Ukrainian).
  23. Vovk M.I., Galyan Ye.B. Restoring of motor component of speech based on muscle movement control. Theoretical grounding. Kibernetika i vyčislitelnaâ tehnika. 2012. № 167. P. 51–60 (in Russian).
  24. The way to treat speech desorders: pat. UA, A61N 1/36, no. 111388, claimed 03.06.2014, publshed 25.04.2016, Bulletin no 18 (in Ukrainian).
  25. Galyan Ye.B. Specialized software module of speech rehabilitation technology, architecture and functional interaction of its components. Control Systems and Machines. 2014. Iss. 6. P. 52–58 (in Russian).
  26. Vovk M.I., Galyan Ye.B. Organization of Intelligent Hand Movements Control to Restore Speech. Kibernetika i vyčislitelnaâ tehnika. 2016. Iss. 184. P. 25–43 (in Russian).
  27. Vovk M.I., Peleshok S.R., Galyan Ye.B. Ovcharenko M.A. The method of assessment of motor and sensory speech disorders. Collected papers of scientific-information center “Knowledge” based on XІ International correspondence scientific-practical conference: «The development of science in the XXI century», part 3. Kharkiv: collected papers. D.: scientific-information center “Knowledge”, 2016. p. 70–76 (in Russian).

Recieved 28.12.2016

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Issue 1 (187), article 3

DOI: https://doi.org/10.15407/kvt187.01.030

Kibern. vyčisl. teh., 2017, Issue 1 (187), pp.30-49

Pavlov V.V., Doctor of Technics, Professor, Head of Intellectual Control Department
Shepetukha YU.M., PhD (technics), Senior Researcher, Senior Researcher of Intellectual Control Department
e-mail: yshep@meta.ua
Melnikov S.V., PhD (technics), Senior Researcher, Acting Head of Intellectual Control Department
e-mail: dep185@irtc.org.ua
Volkov A.E., Researcher of Intellectual Control Department
e-mail: alexvolk@ukr.net

International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine

INTELLIGENT CONTROL: APPROACHES, RESULTS AND PROSPECTS OF DEVELOPMENT

Introduction. Intelligent control systems are advanced computerized systems aimed at the modeling and analysis of intelligent tasks as well as the support of human activity in their solving. Therefore, consideration of both conceptual and applied issues of such systems’ development is an important and urgent scientific problem.

The purpose of the paper is to examine existing approaches, current state, important results and prospects for future development of such new scientific direction as intelligent control.

Methods. Artificial intelligence methods, man-machine theory, conflict resolution theory, theory of deterministic chaos, methods of decision support, methods of distributed control of non-linear applied processes.

Results. One may stress two main directions in the field of intelligent control where promising results have been achieved. The first one, related to the creation of intelligent infrastructure, includes development of methods and structures of distributed control as well as examination of non-linear applied processes in objects with variable properties. The second direction, attributed to the creation of intelligent agents, includes elaboration of methods, models and algorithms for real-time decisions related to the efficient control of dynamic objects.

Conclusion. Modern systems of intelligent control should integrate into a single unity three main components such as: traditional control methods, artificial intelligence theory and decision making approach. The main problem is the transformation of conceptual issues of intelligent systems’ creation into concrete technologies and algorithms of control in specific application domains.

Keywords: intelligent control, human-machine system, conflicts theory, non-linearity, uncertainty, net-centricity.

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REFERENCE

1 Zilouchian A., Jamshidi M. Intelligent control systems using soft computing methodologies. Boca Raton: CRC Press, 2001. 492 p.
https://doi.org/10.1201/9781420058147

2 Shtcherbatov I.A. Intelligent control of robot-technical systems in uncertainty conditions. Bulletin of Astrakhan State Technical University. 2010. No1. pp. 73–77 (in Russian).

3 Antsaklis P.J. On intelligent control: report of the IEEE CSS task force on intelligent control. Technical report of the ISIS group No. ISIS 94-001. University of Notre Dame. 1994. 31 p.

4 Albus J.S. On intelligence and its dimensions. Technical report of the ISIS (Interdisciplinary studies of intelligent systems) group No. ISIS 94-001. University of Notre Dame. 1994. P. 11–13.

5 Antsaklis P.J. On autonomy and intelligence in control. Technical report of the ISIS group No. ISIS 94-001. University of Notre Dame. 1994. P. 14–18.

6 Meystel A. On intelligent control, learning and hierarchies. Technical report of the ISIS group No. ISIS 94-001. University of Notre Dame. 1994. P. 14–18.

7 Imam I.F., Kondratoff Y. Intelligent adaptive agents: a highlight of the AAAI-96 workshop. Artificial Intelligence. 1997. No 18(3). P. 75–80.

8 Hess T.J., Rees L.P., Rakes T.R. Using autonomous software agents to create the next generation of decision support systems. Decision Sciences. 2000. Vol. 31. No 1. P. 1–31.
https://doi.org/10.1111/j.1540-5915.2000.tb00922.x

9 Wooldridge M., Jennings N.R. Intelligent agents: theory and practice. The Knowledge Engineering Review. 1995. Vol. 10. No 2. P. 115–152.
https://doi.org/10.1017/S0269888900008122

10 Intelligent infrastructure for the 21st century. VeriSign, Inc. Mountain View, CA,

11 USA. 22 p. URL: http://complianceandprivacy.com/WhitePapers/VeriSign-Intelligent-Infrastructure-for-the-21syt-Century.pdf

12 Vasilyev S.N. From classical automatic control problems to intelligent control. Theory and Systems of Control. 2001. No 1. pp. 5–22 (in Russian).

13 XII International conference on intelligent systems and control “ISC-2009”. (Cambridge, 2009) URL: http://www.allconferences.com/conferences/2008/ 20081208150054.

14 Pavlov V.V., Pavlova S.V. Intelligent control of complex non-linear dynamic systems: analytics of intelligence. Kiev: Nauk. dumka, 2015. 216 p. (in Russian).

15 Nonaka I., G. von Krogh. Tacit knowledge and knowledge conversion: controversy and advancement in organizational knowledge creation theory. Organization Science. 2009. Vol. 20. No 3. P. 635–652.
https://doi.org/10.1287/orsc.1080.0412

16 Pavlov V.V. Fundamentals of ergatic systems theory. Kiev: Nauk. dumka, 1975. 240 p. (in Russian).

17 Pavlov V.V. Conflicts in engineering systems. Kiev: Vyshcha shkola, 1982. 184 p. (in Russian).

18 Pavlov V.V. Synthesis of strategies in man-machine systems. Kiev: Vyshcha shkola, 1989. 162 p (in Russian).

19 Bibichkov A., Pavlov V., Gricenko V., Gubanov S. “Anticon” — a step for the provision of navigation safety. Navigation. 1999. No 3. pp. 42–43 (in Russian).

20 Method and device for computer networks of control of application processes’ high speed cycles: pat. 83118 Ukaine; reg. 08 Semtember 2006 (in Russian).

Recieved 02.10.2016

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Issue 1 (187), article 2

DOI: https://doi.org/10.15407/kvt187.01.011

Kibern. vyčisl. teh., 2017, Issue 1 (187), pp.11-30

L.S. Fainzilberg, Doctor of Engineering, Associate Professor (Docent),
Chief Researcher of Data Processing Department

e-mail: fainzilberg@voliacable.com

International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine

INTERACTIVE SYNTHESIS OF INFORMATION TECHNOLOGY SIGNALPROCESSING WITH LOCALIZED INFORMATION

Introduction. Current task that inevitably arises before the designer of information technology (IT) signal processing with localized information — selection and setup of intelligent computational procedures to ensure an effective transition from the signal distorted by internal and external perturbations to the information products targeted at specific user.

The purpose of the article is to summarize the experience in the development of IT applications for the analysis and interpretation of the signals with localized information using an open tool for the expansion of the instrumental system.

Methods. On the basis of the object-oriented approach and IT tasks analysis, focused
on the extraction of diagnostic information from the distorted signal with a locally-focused features, held decomposition of the general problem of applied IT synthesis in different
applications.

Results. Generalized model of IT analysis and signals of complex shape interpretation has been developed. The development system architecture is proposed, the core of which is based on two abstract classes — a data carrier generalized model (DCM) and the generalized data processing model (DPM). On the basis of the heirs of these classes set up a set of basic computational component, ensuring the recovery of the useful signal monitoring in terms of internal and external disturbances, detection of informative reconstructed signal fragments, analysis of amplitude-time parameters (diagnostic indicators), focusing on the detected fragments and implementation of diagnostic rules, provides an assessment of the state of the object by the calculated characteristics.

Methodology of the experiments evidence with elements of the deductive approach, which is demonstrated by the example of the original evaluation index electrocardiogram is proposed.

Conclusions. The developed instrumental system allows to accelerate the development of the new IT processing of complex shape signals and to improve its effectiveness. Examples of the successful synthesis of applied information technologies for processing signals with localized information created using the developed instrumental system are given.

Keywords: information technology, complex shape signals, instrumental system.

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REFERENCE

1 Fainzilberg L.S. Information technology for signal processing of complex shape. Theory and practice. Kiev: Nauk. Dumka, 2008. 333 p (in Russian).

2 Gritsenko V.I., Fainzilberg L.S. Computer diagnostics using complex-form signals under conditions of internal and external disturbances. Reports of the NAS of Ukraine. 2013. No 12. P. 36–44 (in Russian).

3 Technology. Soviet Encyclopedic Dictionary. Moscow: Sovetskaya entsiklopediya, 1988. P. 1330 (in Russian).

4 Fainzilberg L.S. Intelligent features and development prospects of fazagraphy — information technology processing complex shape signals. Kibernetika i vycislitelnaa tehnika. 2016. Iss. 186. P. 56–77 (in Russian).

5 Fainzilberg L.S. Computer diagnostics by phase portrait of electrocardiogram. Kiev: Osvita Ukrainy, 2013.191 p. (in Russian).

6 Fainzilberg L.S. Tool system for experimental evaluation of the effectiveness of processing algorithms for signals of complex shape. Control systems and machines. 2008. Vol. 2. P. 3–12, 53 (in Russian).

7 Zenkin A.A. Cognitive Computer Graphics. Moscow: Nauka, 1991. 192 p. (in Russian).

8 Fainzilberg L.S. Nowa metoda interpretacji zapisu EKG w balaniach skriningowych oraz w opiece domowej. Zdrowie publiczne (Public Health). 2005. Vol. 115. No 4.P. 458–464.

9 Fainzilberg L.S., Glushauskene G.A. Narrow-band Rejection Filter for Suppression of Harmonic Concentrated Interference on the Basis of Discrete Fourier Transform . Journal of Automation and Information Sciences. 2009. Vol. 41. Iss. 8. P. 55–70.

10 Fainzilberg L.S. Adaptive smoothing of noise in information technology processing of physiological signals. Mathematical Machines and Systems. 2002. No 3. P. 96–104.(in Russian).

11 Fainzilberg L.S. Restoration of a standard sample of cyclic waveforms with the use of the Hausdorff metric in a phase space. Cybernetics and Systems Analysis. 2003. No 3. P. 20–28 (in Russian).

12 Minzer O.P. Theory and practice of evidence-based medicine. Diagnosis and treatment. 2004. No 3. P. 7–15 (in Russian).

13 Fainzilberg L.S. FASEGRAPH — efficient information technology of ECG processing in the problem of ischemic cardiac disease screening. Clinical Informatics and Telemedicine. 2010.Vol. 6. Iss. 7. P. 22–30 (in Russian).

14 Schijvenaars B.J.A, Van Herpen G., Kors J.A. Intraindividual variability in electrocardiograms. Journal of Electrocardiology. 2008. Vol. 41. Iss. 3. P. 190–196.
https://doi.org/10.1016/j.jelectrocard.2008.01.012

15 Fainzilberg L.S. Simulation models of generating artificial cardiograms in terms of internal and external disturbances. Journal of Qafgaz University — Mathematics and Computer Science. 2012. No 34. P. 92–104 (in Russian).

16 Method for verification of metrological characteristics of digital electrocardiographs: UA Patent 100330:MPK G01 D21/00. No a 2011 11909, Bul. No 23. P. 6. 2012 (in Ukrainian).

17 Gritsenko V.I., Fainzilberg L.S. Personified digital medicine tools — step to health. Herald of the NAS of Ukraine. 2012. No 8. P. 62–70 (in Ukrainian).

18 Gritsenko V.I., Fainzilberg L.S. FASEGRAPH — information technology for the integrated assessment of the cardiovascular system state of the electrocardiogram phase portrait. Information technologies for the Physician. 2013. No 3. P. 52–63 (in Russian).

19 Vasetsky Y.M., Fainzilberg L.S., Chaikovsky I.A.Methods of structure analysis of current distribution in conducting medium for magnetocardiography. Electronic modeling. 2004. No 3. P. 95–115 (in Russian).

20 Fainzilberg L.S. Diagnostics of object state by phase trajectories of observed signals with locally concentrated features. Problems of Control and Informatics. 2004. No 2. P. 56–67 (in Russian).

21 Fainzilberg L.S., Kondratyuk T.V., Semergey N.A. ANTISTRESS — A New Information Technology for the Management of Regulatory Systems of a Human Body Based on the Biofeedback. Control systems and machines. 2011. No 3. P. 62–72 (in Russian).

22 Fainzilberg L.S., Korchynska Z.A., Semerhey M.O.Program-technical complex for study of a new method for biometric identification by phase portrait of electrocardiogram. Forensic Herald. 2015. No 1(23). P. 63–71 (in Ukrainian).

Recieved 22.12.2016

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Issue 1 (187), article 1

DOI: https://doi.org/10.15407/kvt187.01.005

Kibern. vyčisl. teh., 2017, Issue 1 (187), pp.5-11

Grytsenko V.I., Corresponding Member of NAS of Ukraine, Director of International
Research and Training Center for Information Technologies and Systems of National
Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine

e-mail: vig@irtc.org.ua

20 YEARS OF THE INTERNATIONAL RESEARCH AND TRAINING CENTER FOR INFORMATION TECHNOLOGIES AND SYSTEMS

May 5, 1997 the International Research and Training Center for Information Technologies and Systems NAS and MES of Ukraine was established by National Academy of Sciences of Ukraine.

During 20 years new scientific direction — Intelligent Information Technology (IIT), was formed. This methodology, the software and hardware became the basis for the deve-lopment of IIT of imaginative thinking, neural network technology, IIT for digital medicine, the E-education and intelligent control technologies.

The basic directions of fundamental and applied scientific research in the International Center are: creation of intelligent information technologies based on methods and means of imaginative thinking, comprehensive research of problems of intelligent management, intelligent robotics, digital medicine, e-learning, digital information space and technologies for the development of a secure information society.

By the main directions of the International Center, scientific schools in the field of information technologies and systems, technical cybernetics, biological and medical cybernetics, and mathematical analysis of comprehensive economic systems have been formed. An important contribution to the development of these scientific schools was made by outstanding Ukrainian scientists — academicians V.I. Skurikhin, A.G. Ivakhnenko,
N.M. Amosov and A.A. Bakaev. Their students and followers successfully develop these scientific directions in our country and abroad.

The International Center is the initiator of research and development of the concept of a new class of information technologies — intelligent information technologies. These are special, knowledge-intensive information technologies that differ from the known IT in the new quality — operating images of information objects. At the same time, an understanding of human speech, recognition of real and artificially created objects, active interaction with the environment, revealing the essence of the phenomenon, operating knowledge and the choice of strategy and tactics for achieving the set goal are achieved through the contours of intellectual IT.

Technical Committee for Standardization of information technologies, scientific journals “Control Systems and Computers” and “Cibernatics and Computer Engineering”, presentations of our scientists at prestigious international conferences, symposia and exhibitions make an important contribution for increasing the authority of the International Center.

The International Center has formed a program of work for the nearest years and defined the mechanisms for its implementation in the context of the rapid development of intellectualization of information technologies in all spheres of our society. As the comprehensive analysis showed, this program fully corresponds to global trends that the term “digital transformation” characterizes and covers the research priorities in information technology for a period of 5–10 years.

Keywords: intelligent information technology, imaginative thinking, intelligent management, digital medicine, e-learning, robotics, information society.

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ISSUE 1 (187)

DOI: https://doi.org/10.15407/kvt187.01

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TABLE OF CONTENTS:

Grytsenko V.I.
20 Years of the International Research and Training Center for Information Technologies and Systems

Informatics and Information Technologies:

Fainzilberg L.S.
Interactive Synthesis of Iinformation Technology Signalproces-sing with Localized Information

Intellectual Control and Systems:

Pavlov V.V., Shepetukha YU.M., Melnikov S.V., Volkov A.E.
Intelligent Control: Approaches, Results and Prospects of Development

Vovk M.I.
Bioengineering Systems for Human Motor Functions Control

Medical and Biological Cybernetics:

Kovalenko A.S., Kozak L.M., Romanyuk O.A.
Information Technology of Digital Medicine

Kiforenko S.I.
Hierarchical Modeling as the Basis of Technology of Preclinical Testing Blood Glucose Level Control Algorithms

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Issue 186, article 7

DOI:https://doi.org/10.15407/kvt186.04.078

KVT, 2016, Issue 186, pp.78-94

UDС 615.47; 004.9

NEW OPPORTUNITIES FOR MOVEMENT AND SPEECH REHABILITATION

Vovk M.I.

International Research and Training Center for Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kiev, Ukraine

dep140@irtc.org.ua

Introduction. Movement training is one of the main factors to mobilize person’s reserves at movement restoration.

The purpose of this article is to show the role of new bioinformatics technology and digital medical devices, original methods, programs and techniques of movement training of the limbs and fine motor hand, to restore motor and speech functions in patients after stroke.

Results. The bioinformatics technology TRENAR® for motor and speech rehabilitation is presented. The technology uses various programs (models) and methods for forced and voluntary movement training that are based on special   EMG signals processing and their transformation into informative visual and sound signals, that define movements. Structural – functional models of damaged motor area of the cortex reorganization aimed at motor control restoration according to movement training programs “Synthesis” (artificially synthesized programs of electric stimulation), “Donor” (programs are based on voluntary contractions of healthy muscles of a patient), “Biotraining” (Biofeedback method) are described. The technology is implemented in two electronic devices of digital medicine Trenar-01 and Trenar-02. New method and technology to restore speech on the basis of original techniques of fine motor hand training and technology TRENAR® are described. The results of clinical testing of technology in motor and speech restoration of patients after the stroke are presented.

Conclusion. The main benefits of the technology TRENAR® which lead to an increase in efficiency of motor and speech rehabilitation are as follows: advanced range of training programs, based on different methods, original techniques of fine motor hand training allows one to select individual approach to rehabilitation process.

Keywords: bioinformatics technology, digital medicine, electronic devices, programmed electric stimulation, biofeedback, rehabilitation, movement, hand, speech, stroke, individual approach.

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Reference

1 Belova A.N., Prokopenko S.V. Neurorehabilitation. 3th ed. Moscow, 2010, 1288 p. (in Russian).

2 Aleev L., Vovk M., Gorbanev V. & others. “Mioton” in motor control. Kiev, 1980, 142 p. (in Russian).

3 Aleev L. S., Vovk M.I. Functional electrostimulation with myofeedback in movement rehabilitation. Proc. “5th International Muscle Symposium” (May 19-21, 2000, Viena, Austria). Viena, 2000, pp.69-70.

4 Gritsenko V.I., Kotova A. B., Vovk M. I. & others. Information technology in Biology and Medicine. Lecture course. Kiev, 2007, pp. 285-340 (in Ukrainian).

5 Vovk M.I. Bioinformatic technology of movements control as the direction of biological and medical cybernetics. Kibernetika i vycislitel’naa tehnika, 2013, No 174, pp. 56–70. (in Russian).

6 Gritsenko V.I., Vovk M.I. “TENAR” – innovational technology of movements restoring Materials of the International scientific – practical forum ” The Science and Business – a basis of development of economy ” . Dnepropetrovsk, 2012, pp.204-206. (in Russian).

7 Hunter P. Peckham, Kevin L. Kilgore, “Challenges and Opportunities in Restoring Function after Paralyses. IEEE Trans. Biomed. Eng.2013, Vol. 60, No .3, pp. 602-609.

8 Romanov S.P. Neurophysiological mechanisms of motor functions homeostasis / Doctor in Biology: specialty. 03.00.13. St. Petersburg, 1989, 443 p. (in Russian).

9 Anohin P.K. The Sketches on Physiology of Functional Systems. M.: Medicine, 1975, 447 p. (in Russian).

10 The method of Motor Control of a Person. Patent 41 795 Ukraine. 10.06.2009. (in Ukrainian).

11 Electrical stimulator. Patent. 32376 Ukraine: 12 .05. 2008. (in Ukrainian).

12 The Inventor’s Certificate on author’s product right 26 836 Ukraine. The Device for Electrical Stimulation with Biocontrol Trenar-01. The Technique for Using / M. Vovk, V. Ivanov, A. Shevchenko / 09.12.2008. (in Ukrainian).

13 Vovk M., Gorbanev V., Shevchenko A. The Inventor’s Certificate on author’s product right 37243 Ukraine. The Device for Electrical Stimulation with Biofeedback Trenar-02. The Technique for Using . 04.03.2011. (in Ukrainian).

14 Koltsova M.M. Motor activity and development of the child’s brain functions. Moscow: “Pedagogika”, 1973. 143 p. (in Russian).

15 Vovk M.I. , Galyan Ye. B. Restoring of motor component of speech based on muscle movement control. Theoretical grounding . Kibernetika i vycislitel’naa tehnika, 2012, Is. 167, pp.51-60. (in Russian).

16 16. The way to treat speech desorders. UA, A61N 1/36, no. 111388, 2016.(in Ukrainian).

17 Halverson H. M. The acquisition of skill in infancy. Journal of Genetic Psychology. 1933, Vol. 43, pp. 3-48. https://doi.org/10.1080/08856559.1933.10533118

18 Vovk M.I. , Galyan Ye. B. Organization of Intelligent Hand Movements Control to Restore Speech. Kibernetika i vycislitel’naa tehnika, 2016, Is. 184, pp.25-43. (in Russian).

19 Galyan Ye.B. Specialized software module of speech rehabilitation technology, architecture and functional interaction of its components. Control Systems and Machines, 2014, No 6, pp. 52-58. (in Russian).

20 Vovk M.I., Peleshok S.R., Galyan Ye.B. & others The method of assessment of motor and sensory speech disorders. Collected papers of scientific-information center “Knowledge” based on XI International correspondence scientific-practical conference: “The development of science in the XXI century” part 3. Kharkiv: collected papers. D, 2016, pp. 70-76. (in Russian).

Received 03.10.2016