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Issue 4 (194), article 3

DOI:https://doi.org/10.15407/kvt194.04.041

Kibern. vyčisl. teh., 2018, Issue 4 (194), pp.

Stepashko V.S., DSc (Engineering), Professor,
Head of Dep. for Information Technologies of Inductive Modeling
e-mail: stepashko@irtc.org.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,
Acad. Glushkov av., 40, Kyiv, 03187, Ukraine

FORMATION AND DEVELOPMENT OF SELF-ORGANIZING INTELLIGENT TECHNOLOGIES OF INDUCTIVE MODELING

Introduction. Effective solution of control and decision-making tasks in complex systems should use the results of mathematical modeling. To construct adequate predictive models, many modern methods and tools are available which may be generally based on two principal approaches: theory-driven (deductive) and data-driven (inductive) ones. The data-driven methods are basic for solving typical tacks of data mining; they implement an inductive process of transition from particular data to models generalizing the data. Among all such methods, very notable are those being developed within the area of GMDH-based inductive modeling founded several decades ago by academician O.H. Ivakhnenko.

The purpose of this paper is analysing the background of the GMDH invention by Ivakhnenko and the evolution of model self-organization ideas, methods and tools during the half-century historical period of successful development of the inductive modeling methodology.

Results. Professor Ivakhnenko acquired broad knowledge in the areas of automatic control, engineering cybernetics and emerging neuroscience initiated by the idea of percep-tron. These were those prerequisites which helped Ivakhnenko to synthesize his original self-organizing approach to solving tasks of constructing models of objects and processes on the basis of experimental data. The paper tracks evolution of scientific ideas and views of Ivakhnenko and main achievements in development of GMDH during the period 1968-1997. Contributions of researchers from different countries to the GMDH modification and application are characterized. Results of further developments of inductive modeling meth-ods and tools in the ITIM department are presented and the most promising prospects of in-vestigations in this field are indicated.

Conclusions. Main prerequisites facilitating the creation of the GMDH by O.H. Ivakhnenko were analysed, basic fundamental, technological and applied achievements of the half-century development of inductive modeling both in Ukraine and abroad were characterized, as well as the most prospective ways of further research were formulated.

Keywords: mathematical modeling, data-driven modeling, model self-organization, GMDH, inductive modeling, noise-immune modeling, information technology, case study.

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Received 20.09.2018

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Issue 4 (194), article 2

DOI:https://doi.org/10.15407/kvt194.04.029

Kibern. vyčisl. teh., 2018, Issue 4 (194), pp.

Yermakova I.I., Professor, DSc (Biology),
Leading Researcher Dept. of Complex Research
of Information Technologies
e-mail: : irena.yermakova@gmail.com

Nikolaienko A.Y., Researcher,
Dept. of Complex Research of Information Technologies
e-mail: n_nastja@ukr.net

Solopchuk Y.M., Researcher,
Dept. of Complex Research of Information Technologies

Hrytsaiuk O.V., 1st category software engineer,
Dept. of Complex Research of Information Technologies

Tadeieva J.P., Ph.D. (Engineering), Senior Researcher,
Dept. of Complex Research of Information Technologies

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,
Acad. Glushkova av., 40, Kiev, 03187, Ukraine

INFORMATION SMARTPHONE TECHNOLOGY FOR PREDICTION OF HUMAN HEALTH STATE UNDER EXTREME ENVIRONMENTAL CONDITIONS

Introduction. Nowadays it can’t be imagined the development of personalized e-medicine without smartphone use. It involves the integration of information platforms, mobile applications and portable medical devices via cloud technologies into a single system. Predictive systems that can assess and prevent risk factors of human health in extreme environmental conditions is still absent in contemporary mobile personalized medicine. Combining the unique features of the service platform with the recent development of m-health allows to develop a unique information smartphone system for assessing the risk factors of human health in various environmental conditions. The system allows to collect personal data, integrate the data with another mobile app and gadget data and thus provide predictions of the human state.

The purpose of the article is to develop an intelligent information system
using smartphone technologies based on a multi-functional service platform for predicting a human functional state under extreme environmental conditions.

Results. A client-server architecture was used to build the intelligent information smartphone system, which allows a user to access the service platform (a key feature of the system) and a centralized database via the smartphone application.
The “client” is the smartphone application that uses network protocols to exchange data with the server. Data input, primary control and data transfer to the server, as well as receiv-ing and displaying the prediction results on the smartphone screen are the main functions of the app. The server software provides data management (receiving, processing, transferring and storing data in the databases), automatically controls the integrity and consistency of the information received and stored, manages multi-user access and confidentiality of databases of different users, logs system events, etc.
A unique distinctive feature of the developed system is the service platform for process-ing the entered conditions data and giving the prediction of human functional state. The pre-diction results are analyzed and, based on the results of the analysis, the system identifies probable health risk factors. The automatic analysis and decision making allow to classify the developed system as an intelligent information technology.

Conclusions. The smartphone-health system has been developed. The system has a client-server architecture that provides multi-user access to its resources and features.
The “client” is a smartphone application that allows a user to input, control and transfer the data to the server, and then receive and display the results on the screen. The server con-sists of a data flow manager, the service platform, prediction result database. The multifunc-tional service platform provides a user with the prediction of his functional state under chosen environmental conditions and physical activity.

Keywords: smartphone, e-health, human state prediction, mobile health, extreme environmental conditions.

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Received 31.08.2018

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Issue 4 (194), article 1

DOI:https://doi.org/10.15407/kvt194.04.007

Kibern. vyčisl. teh., 2018, Issue 4 (194), pp.

Grytsenko 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
e-mail: vig@irtc.org.ua

Rachkovskij D.A., DSc (Engineering), Leading Researcher
Dept. of Neural Information Processing Technologies
e-mail: dar@infrm.kiev.ua

Revunova E.G., PhD (Engineering), Senior Researcher
Dept. of Neural Information Processing Technologies
e-mail: egrevunova@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,
Acad. Glushkov av., 40, Kiev, 03187, Ukraine

NEURAL DISTRIBUTED REPRESENTATIONS OF VECTOR DATA IN INTELLIGENT INFORMATION TECHNOLOGIES

Introduction. Distributed representation (DR) of data is a form of a vector representation, where each object is represented by a set of vector components, and each vector component can belong to representations of many objects. In ordinary vector representations, the meaning of each component is defined, which cannot be said about DR. However, the similarity of RP vectors reflects the similarity of the objects they represent.
DR is a neural network approach based on modeling the representation of information in the brain, resulted from ideas about a “distributed” or “holographic” representations. DRs have a large information capacity, allow the use of a rich arsenal of methods developed for vector data, scale well for processing large amounts of data, and have a number of other advantages. Methods for data transformation to DRs have been developed for data of vari-ous types – from scalar and vector to graphs.

The purpose of the article is to provide an overview of part of the work of the Department of Neural Information Processing Technologies (International Center) in the field of neural network distributed representations. The approach is a development of the ideas of Nikolai Amosov and his scientific school of modeling the structure and functions of the brain.

Scope. The formation of distributed representations from the original vector representations of objects using random projection is considered. With the help of the DR, it is possible to efficiently estimate the similarity of the original objects represented by numerical vectors. The use of DR allows developing regularization methods for obtaining a stable solution of discrete ill-posed inverse problems, increasing the computational efficiency and accuracy of their solution, analyzing analytically the accuracy of the solution. Thus DRs allow for in-creasing the efficiency of information technologies applying them.

Conclusions. DRs of various data types can be used to improve the efficiency and intelligence level of information technologies. DRs have been developed for both weakly structured data, such as vectors, and for complex structured representations of objects, such as sequences, graphs of knowledge-base situations (episodes), etc. Transformation of different types of data into the DR vector format allows unifying the basic information technologies of their processing and achieving good scalability with an increase in the amount of data processed.
In future, distributed representations will naturally combine information on structure and semantics to create computationally efficient and qualitatively new information technologies in which the processing of relational structures from knowledge bases is performed by the similarity of their DRs. The neurobiological relevance of distributed representations opens up the possibility of creating intelligent information technologies based on them that func-tion similarly to the human brain.

Keywords: distributed data representation, random projection, vector similarity estimation, discrete ill-posed problem, regularization.

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Issue 4 (194)

DOI:https://doi.org/10.15407/kvt194.04

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TABLE OF CONTENTS:

100th Anniversary of the National Academy of Sciences of Ukraine

Informatics and Information Technologies:
Grytsenko V.I., Rachkovskij D.A., Revunova E.G.
Neural Distributed Representations of Vector Data in Intelligent Information Technologies

Yermakova I.I., Nikolaienko A.Y., Solopchuk Y.M., Hrytsaiuk O.V., Tadeieva J.P.
Information Smartphone Technology for Prediction of Human Health State Under Extreme Environmental Conditions

Intelligent Control and Systems:

Stepashko V.S.
Formation and Development of Self-Organizing Intelligent Technologies of Inductive Modeling

Medical and Biological Cybernetics:

Kozak L.M., Kovalenko A.S., Krivova O.A., Romanyuk O.A.
Digital Transformation in Medicine: From Formalized Medical Documents to Information Technologies of Digital Medicine

Vovk M.I.
Information Technology of Movement Control. Evolution of Synthesis and De-velopment Prospects

Information messages

100th anniversary of the Academician of the National Academy of Sciences of Ukraine BORIS PATON

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Issue 3 (193), article 5

DOI:https://doi.org/10.15407/kvt192.03.083

Kibern. vyčisl. teh., 2018, Issue 3 (193), pp.

Kiforenko S.I.1, DSc (Biology), Senior Researcher,
Leading Researcher of Dep. of Application Mathematical
and Technical Methods in Biology and Medicine
e-mail: skifor@ukr.net

Hontar T.M.1, PhD (Biology), Senior Researcher,
Dep. of Application Mathematical and Technical Methods in Biology and Medicine
e-mail: gtm_kiev@ukr.net

Ivaskiva K.Y.2, PhD (Medicine), Senior Researcher,
Scientific-advisory of Dep. of Ambulatory and Preventive Care for Patients with Endocrine Pathology
e-mail: _k_iva@ukr.net

Obelets T.A.3, Computer Systems Analyst
e-mail: obel.tet@gmail.com

1 International Research and Training Centre for Information Technologies
and Systems of the National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Glushkov ave., 40, Kyiv, 03187, Ukraine

2 State Institution “V.P. Komisarenko Institute of Endocrinology and Metabolism of NAMS of Ukraine”, 69, Vyshgorodska St., Kyiv, 04114, Ukraine

3 National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Peremogy av. 37, Kyiv, 03056, Ukraine

INFORMATIONAL DECISION SUPPORT SYSTEM FOR MONITORING AND CORRECTING SOMATIC HEALTH

Introduction. Somatic health is the most important component of human health. It is the physical status that has a responsible role in the material and energy provision of the functioning of the physiological systems of the organism and their maintenance within the boundaries of the homeostatic norm. Emphasis on the motivation and self-control of their health, on an adequate orientation in the use of modern health-saving technologies is relevant.

The purpose of the article is to create a decision support system for increasing awareness of the health status and improve the efficiency of correcting the state of somatic health by using modern computer and mobile technologies.

Methods. The paper describes the information technology of quantitative assessment and correction of a person’s physical health, which is based on the information-structural model of a person’s physical health. A software-algorithmic complex for use in personal computers and mobile applications to support decision-making in the selection of recreational activities has been developed.

Results. The information structure of physical health was developed from the viewpoint of management theory, taking into account the subjective-objective aspects of evaluation and the multidimensionality of the research object. To support decision making in assessing health status and selecting preventive measures, a set of computer programs “HEALTH-ENERGY BALANCE ” has been developed. The basis of the complex is the modules “Early Diagnosis” — for assessing the condition and “Energobalance” — to support decision making when choosing a balanced diet, adequate activity and daily energy costs. Given the current trends in the development of the mHealth industry, this software is adapted for use in mobile devices.

Conclusion. The developed technology allows, using non-invasive techniques, to quantify the state of physical health. Depending on the position of the evaluation criterion on the diagnostic scale, the user is given the opportunity to choose the appropriate recreational techniques and minimize the mismatch between the energy value of the food ration and energy expenditure in selecting the activity mode. Implementation of the developed algorithms in mobile Android applications to the smartphone increases the effectiveness of supporting independent decision-making when organizing the life of the user.

Keywords: somatic health, automated information technology, objectively-subjective evaluation, software, mobile applications.

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REFERENCES
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Recieved 03.06.2018

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Issue 3 (193), article 4

DOI:https://doi.org/10.15407/kvt192.03.064

Kibern. vyčisl. teh., 2018, Issue 3 (193), pp.

Shakhlina L.Ya.-G.1, DSc. (Medicine), Professor,
Professor of Sport Medicine cafedra
e-mail: sportmedkafedra@gmail.com

Aralova N.I.2, PhD. (Engineering),Senior Researcher,
Senior Researcher of Dept. of Optimization of Controlled Processes
e-mail: aralova@ukr.net

1 National University of Physical Education and Sport of Ukraine
Fiscultury Street, 1, Kiev, 03150, Ukraine

2 Institute of Cybernetics of National Academy of Science of Ukraine, Acad.Glushkov av., 40, Kiev, 03187, Ukraine

FORECASTING THE ORGANISM REACTION OF THE ATHLETES ON INHIBITING HYPOXIC MIXTURES ON THE MATHEMATICAL MODEL OF THE FUNCTIONAL RESPIRATION SYSTEM

Introduction. In the modern sports of higher achievements, the issues of training and competitive activity of athletes using the hypoxic factor in natural-mountain conditions or with artificial hypoxic training with the use of pressure chambers or hypoxicators continue to attract great interest among specialists in the field of physiology, medicine, sports pedagogy. The influence of reproductive hormones on the functional breathing system responsible for the aerobic capacity of the female body remains insufficiently studied. There are no scientifically substantiated programs for training athletes, mainly developing the quality of endurance, in conditions of hypoxic hypoxia, taking into account the phases of the menstrual cycle.

The purpose of the article is to determine the reaction of the functional breathing system and to reveal the degree of tissue hypoxia in athletes when inhaled hypoxic gas mixture with 11% oxygen in different phases of the menstrual cycle.

Results. On the mathematical model of the functional breathing system, based on physiological examination data, an imitation of a hypoxic mixture with athletes was performed with athletes of 11% oxygen in different phases of the menstrual cycle. The partial pressures and voltages of oxygen in alveolar air, arterial and mixed venous blood, heart, brain and skeletal muscle tissues were calculated. Numerical experiments were also performed with the replacement of the real values of the minute volume of respiration and the minute volume of blood in the corresponding phases of MC for adaptation processes in other phases of the cycle.

Conclusions. The results of the prediction on the mathematical model of the respiratory system of the athlete’s reactions to the inhalation of hypoxic mixtures testify to the specificity of functional self-regulation and, consequently, the adaptive capabilities to the hypoxia of the female body during cyclic changes in the hormonal status in different phases of the menstrual cycle. The results of preliminary studies show that under hypoxic conditions, as a result of inhalation of a gas mixture with 11% oxygen without a compenetration increase in pulmonary ventilation and systemic circulation, the oxygen tension in the body tissues may be below the critical level and with different degrees of expression in different phases of the MC, which is confirmed by the presented results of calculation on a mathematical model of oxygen tension in the studied tissues.

The obtained results testify to the need for further study of the individual reactions of the organism of athletes in conditions of hypoxia for the scientific substantiation of sports training for women taking into account the biological characteristics of their organism.

Keywords: mathematical model of the functional breathing system, training process of athletes, interval hypoxic training, phases of the menstrual cycle, functional self-organization of the organism

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Received 04.05.2018

admin

Issue 3 (193), article 3

DOI:https://doi.org/10.15407/kvt192.03.043

Kibern. vyčisl. teh., 2018, Issue 3 (193), pp.

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

Galyan Ye.B., PhD (Engineering), Researcher,
Bioelectrical Control & Medical Cybernetics Dep.
e-mail: galian@irtc.org.ua

Kutsyak A.А., PhD (Engineering), Researcher,
Bioelectrical Control & Medical Cybernetics Dep.
e-mail: spirotech85@ukr.net

Lauta A.D., PhD (Medicine), Senior Researcher,
Bioelectrical Control & Medical Cybernetics Dep.
e-mail: dep140@irtc.org.ua

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

FORMATION OF INDIVIDUAL COMPLEX OF CONTROL ACTIONS FOR MOTOR AND SPEECH REHABILITATION AFTER A STROKE

Introduction. At present, one of the leading directions in the healthcare system is an individual approach to treatment. Restoration of movements and oral speech after a stroke suggests the formation of an individual complex of control actions – programs, techniques for general limb movements, fine motor hand training to reduce the deficit of motor and speech functions acquired as a result of pathology.

The purpose of the article is to determine on the basis of which algorithms, the informative criteria for estimating the deficit of motor and speech functions, as well as rules to be solved, an individual set of movements, programs and training schedule to restore motor and speech functions after a stroke are formed.

Results. A general and additional algorithms for the formation of an individual complex of control actions for motor and speech functions rehabilitation after a stroke have been developed. According to the algorithms, the patient is tested for general and specific contraindications to the use of muscle electrical stimulation and / or biofeedback training, quantitative assessment of motor and speech functions, muscle tonus according to new original techniques, verification of limitations to the application of programs and the duration of training. Additional algorithms are designed taking into account both hyper- and hypotonic parameters. A special feature of these algorithms is the introduction of additional restrictions, for which intervals of muscle tone values are formed.

Decision rules have been developed using the algebra of predicates, logical variables corresponding to the specified criteria and indicators. According to these rules, in each stage of rehabilitation, a set of movements and training programs recommended by priority (“Synthesis”, “Donor”, “Threshold”, “Biofeedback” according to TRENAR® technology) and their schedule are determined in binary form.

Conclusions. The considered approach to the formation of an individual complex of control actions for movement and speech rehabilitation after a stroke is the theoretical basis to synthesize the mobile information technology of digital medicine for assistance the physician in diagnosing and carrying out individual rehabilitation of motor and speech functions after a stroke.

Keywords: stroke, movement, speech, rehabilitation, quantitative assessment, algorithm, decision rules, individual control actions, programs, electrical muscle stimulation, biofeedback training.

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Received 4.06.2018

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Issue 3 (193), article 2

DOI:https://doi.org/10.15407/kvt192.03.027

Kibern. vyčisl. teh., 2018, Issue 3 (193), pp.

Antomonov M.Y., DSc (Biology), Professor,
Chief Researcher of the Laboratory of Epidemiological Research and Medical Informatics
e-mail: antomonov@gmail.com
State Institution “O.M. Marzіeiev Institute for Public Health of the National Academy of Medical Sciences of Ukraine”, 50,  Popudrenko str.  Кyiv, 02660

INFORMATION TECHNOLOGY FOR CONSTRUCTING THE COMPOSITE INDICES FOR DATA OF DIFFERENT TYPES USED IN MEDICAL AND ENVIRONMENTAL STUDIES

Introduction. Information technologies used in medical and environmental researches often deal wiht huge amounts of information processing. These technologies allow us to identify and investigate previously hidden dependencies and interactions in complex environmental, medical and biological systems, and on the other hand, it is accompanied by the analysis of large data sets, some of which (sometimes most of them) have an uninformative (noisy) character. One of the ways of solving this problem are the methods of constructing composite indices (CI), i.e. complex indicators, which allow to perform an integral assessment of the state and functioning of ecological, medical and biological systems.

The purpose of the paper is to develop a generalized information technology for constructing composite indices for different types of data used in medical and environmental studies.

Results. Medical and ecological researches include two main components: analysis of the states of both human health and of the environment; in solving such problems it is necessary to evaluate and analyze the state of the bioobject according to the data of different types: quantitative, rank, binary and qualitative variables. The developed general information technology is oriented on supporting the solution of a wide range of medical and hygienic tasks and integrates various approaches to processing and analysing of data of different types. Proposed technology consists of four stages: the formation and initial analysis of an initial indicators set, the calculation and normalization for obtainig unnamed equivalents, the actual design of the composite indices, and their verification. The implementation of this technology makes it possible to compare data of different dimensions, determine the significance of specific characteristics in a general research totality, to evaluate the integral state and to classify the research objects.

Conclusion. The proposed information technology for the construction of composite indices based on data of different types: quantitative, rank, binary and qualitative variables, is an effective tool for determining and comparing the state of bioobjects of different nature, and its use makes it possible to avoid mistakes in the incorrect application of mathematical methods for processing medical and ecological information.

Keywords: information technology, composite indicators, processing medical and ecological quantitative, rank, binary and qualitative variables.

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Resieved 11.06.2018

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Issue 3 (193), article 1

DOI:https://doi.org/10.15407/kvt192.03.005

Kibern. vyčisl. teh., 2018, Issue 3 (193), pp.

Revunova E.G., Ph.D. (Engineering),
Senior Researcher Department of Neural Information Processing Technologies
e-mail: egrevunova@gmail.com

Rachkovskij D.A., DSc. (Engineering),
Leading Researcher, Department of Neural Information Processing Technologies
e-mail: dar@infrm.kiev.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,
Acad. Glushkova av., 40, Kiev, 03187, Ukraine

RANDOM PROJECTION AND TRUNCATED SVD FOR ESTIMATING DIRECTION OF ARRIVAL IN ANTENNA ARRAY

Introduction. The need to solve inverse problems arises in many areas of science and technology in connection with the recovery of the object signal based on the results of indirect remote measurements. In the case where the transformation matrix has a high conditional number, the sequence of its singular numbers falls to zero, and the output of the measuring system contains noise, the problem of estimating the input vector is called discrete ill-posed problem (DIP). It is known that the DIP solution using pseudoinverse of the input-output transformation matrix is unstable. To overcome the instability and to improve the accuracy of the solution, regularization methods are used.

Our approaches to ensuring the stability of the DIP solution (truncated singular decomposition (TSVD) and random projection (RP)) use the integer regularization parameter, which is the number of terms of the linear model. Regularization with an integer parameter makes it possible to provide a model close to the best in terms of the accuracy of the input vector recovery, and also to reduce the computational complexity by reducing the dimensionality of the problem.

The purpose of the article is to develop an approach to estimating the direction of arrival of signals in the antenna array using the DIP solution, to compare the results with the well-known MUSIC method, to reveal the advantages and disadvantages of the methods.

Results. Comparison of TSVD and MUSIC (implemented in real numbers) when working with correlated sources and five snapshots showed the advantage of TSVD in terms of the power of the useful signal Pratio by 2.2 times with the number of antenna elements K = 15 and by 4.7 times with K = 90. The advantage of TSVD in Pratio is by 3.7 times for K = 15 and by 4.2 times for K = 90. Comparison of RP and MUSIC (implemented in real numbers), when working with correlated sources and five snapshots, showed the advantage of RP in Pratio by 3 times at K = 15 and by 4.4 times at K = 90. When working with 100 snapshots, the advantage of RP in Pratio is by 3.8 times for K = 15 and by 4.2 times for K = 90.

Conclusions. The approach to determining the direction of arrival based on the l2-regularization methods provides a stable solution in the case of a small number of snapshots, high noise and correlated source signals. Methods of determining the direction of arrival based on l2-regularization, in contrast to l1-regularization, do not impose restrictions on the properties of the input-output transformation matrix, do not require a priori information on the number of signal sources, allow constructing efficient hardware implementations.

Keywords: Direction of arrival estimation, truncated singular value decomposition, random projection, MUSIC.

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Received 15.05.2018

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Issue 3 (193)

DOI:https://doi.org/10.15407/kvt193.03

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TABLE OF CONTENTS:

Informatics and Information Technologies:
Revunova E.G., Rachkovskij D.A.
Random Projection and Truncated SVD for Estimating Direction of Arrival in Antenna Array

Antomonov M.Y.
Information Technology for Constructing the Composite Indices for Data of Different Types Used in Medical and Environmental Studies

Intellectual Control and Systems:

Vovk M.I., Galyan Ye.B., Kutsyak A.А., Lauta A.D.
Formation of Individual Complex of Control Actions for Motor and Speech Rehabilitation after a Stroke

Medical and Biological Cybernetics:

Shakhlina L.Ya.-G., Aralova N.I.
Forecasting the Organism Reaction of the Athletes on Inhibiting Hypoxic Mixtures on the Mathematical Model of the Functional Respiration System

Kiforenko S.I., Hontar T.M., Ivaskiva K.Y., Obelets T.A.
Informational Decision Support System for Monitoring and Correcting Somatic Health