Category: Issue 1 (199)

Issue 1 (199), article 5

DOI:https://doi.org/10.15407/kvt199.01.085

Cybernetics and Computer Engineering, 2020, 1(199)

Azarkhov O.Yu.¹, DSc. (Medicine),
Head of the Biomedical Engineering Department
e-mail: alexazarhov@gmail.com

Chernyshova T.A.², Physician,
e-mail: tetyana.che@gmail.com

¹Pryazovsky State Technical University of the Ministry of Education and Science of Ukraine,
7, University st., Mariupol, 87555, Ukraine

²Aviation Medical Center of the National Aviation University,
1, Komarova av., Kyiv, 03058, Ukraine

APPLICATION OF INFORMATION TECHNOLOGY FOR DETERMINATION OF CIRCULATING TUMOR CELLS TO DIAGNOSTICS OF MALIGNANT TUMOR DISEASES

Introduction. The study of the possibility of using the circulating tumor cells (CTC) definition in the patients` blood with different localization of malignant tumors as a diagnostic criterion and the criterion of the effectiveness of specific treatment tactics is one of the topical issues in modern oncology.

The purpose of the paper is to analyze the results of using the developed information technology for identification of circulating tumor cells for the study of blood samples of patients in order to confirm or reject the initial diagnosis of cancer of different localization.

Results. Our information technology is based on the use of an advanced method of isolation of intact circulating cells, the difference of which is to supplement the structure of the basic ISET method (Isolation by Sizе of Tumor Cells) with new modes: 100% sealing chamber with hemolysate and providing it with the necessary and constant pressure during the filtration process by introducing a negative pressure gauge, as well as the mode of three-level filtering of the CTC on consecutive polycarbonate membranes with micropore diameters of 8 μm, 5 μm and 3 μm. To assess the malignancy of selected cells, the information technology used the method of determining the CTC according to the set of criteria, formed databases with created template CTC masks and control templates in the automated mode. Blood samples from patients were tested using IT. Taking into account each step of the technique (using different filters), analysis of the results showed that of the total proportion of samples, which additionally detected the CTC using not only an 8 μm filter, but also filters 5 μm and 3 μm, was 20.66 %.

Conclusions. The use of information technology to identify circulating tumor cells improves the efficiency of detecting these cells by reducing the testing time and expanding the range of research due to the ability to detect cells of small size. Improvement of IT by supplementing the knowledge base (complex of template mask masks and relevant expert findings) makes it possible to apply it in screening of patients’ blood, including at the preclinical stage of the examination.

Keywords: information technology, circulating tumor cells, method of isolation of circulating tumor cells, automated system, screening of patients’ blood.

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26. Chernyshova T.A. Criteria and Method for Detection of Circulating Tumor Cells. Cybernetics and computer engineering. 2019, no.1 (195), pp.85-98.
https://doi.org/10.15407/kvt195.01.082

27. Pat. 127486 UA, MPK C12M 3/06, G01N 33/574, G01N 33/49. Device for detecting circulating tumor cells in the blood / S.M. Zlepko, V.E. Krivonosov, S.V. Timchyk, T.A. Chernyshova, O.S. Zlepko, O.Yu. Azarkhov, V.S. Pavlov, V.V. Krivonosov (Ukraine). 2018 00060; claimed 02.01.2018; publ. 08/10/2018, Bul. № 15. – 7 p. (in Ukrainian).

Recieved 11.12.2019

Issue 1 (199), article 4

DOI:https://doi.org/10.15407/kvt199.01.059

Cybernetics and Computer Engineering, 2020, 1(199)

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
e-mail: vig@irtc.org.ua

FAINZILBERG L.S., DSc. (Engineering), Professor,
Chief Researcher of the Department of Intelligent Automatic Systems
e-mail: fainzilberg@gmail.com

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

CURRENT STATE AND PROSPECTS FOR THE DEVELOPMENT OF DIGITAL MEDICINE

Introduction. According to the definition of the International Society of Digital Medicine, digital medicine is a field of science in which scientists strive to explain previously incomprehensible pathophysiological phenomena in the human body and to explore new medical procedures using modern digital technologies to improve the quality of human life.

The purpose of the paper is to provide brief information about the current state and prospects for the development of digital medicine.

Methods. The analysis of the main directions of digital medicine is done. Basic definitions of the concepts “Intelligent IT signal processing” and “Effective computational procedure” are formulated. The role of intelligent IT in digital medicine is demonstrated on the example of fasegraphy method.

Results. Existing methods and means of digital medicine are used for diagnosis, treatment, rehabilitation, as well as to restore the lost functions of the patient (vision, hearing, movement). Such technologies make it possible not only to free medical workers from solving routine tasks, but also to increase the efficiency of performing surgical operations, radiation therapy and a number of other tasks of practical medicine. Unlike traditional IT, based on procedures for processing numerical data, intelligent IT operate with generalized concepts (images) that provide more complete information about the external environment, and the analysis of such images generates a holistic picture of the phenomena studied. Within the framework of the algorithmic approach, the construction of intelligent IT for solving the problems of digital medicine requires the active participation of a technology developer, who, using his natural intelligence, creates effective procedures for extracting diagnostic information from real data under disturbances.

Conclusions. Intelligent IT with the properties of natural intelligence (adaptation, generalization, learning, etc.) play an important role in expanding the functional capabilities and increasing the effectiveness of digital medicine.

Keywords: digital medicine, intelligent IT, efficient computing procedures.

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Received: 06.12.2019

Issue 1 (199), article 3

DOI:https://doi.org/10.15407/kvt199.01.039

Cybernetics and Computer Engineering, 2020, 1(199)

MISHCHENKO M.D., Student
e-mail: mishenkomihailo@gmail.com
National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” 37, Peremohy av., 03056, Kyiv, Ukraine

GUBAREV V.F., DSc. (Engineering), Corresponding Member of NAS of Ukraine,
Head of the Dynamic Systems Control Department
e-mail: v.f.gubarev@gmail.com
Space Research Institute of the National Academy of Sciences of Ukraine and the State Space Agency of Ukraine
40, Acad. Glushkova, 03187, Kyiv, Ukraine

METHODS OF MODEL PREDICTIVE CONTROL FOR DISCRETE MULTI-VARIABLE SYSTEMS WITH INPUT

Introduction. There are a lot of systems which can be conveniently modelled as a discrete linear multi-input multi-variable system. When a control problem for such systems arises, it is usually done with methods derived from the control theory. But these methods have several known drawback. For example, for non-deterministic systems, they are based on assumption about certain convenient statistical properties of noises.

The purpose of the paper is to develop synthesis algorithms based on ideas and approaches of the Model Predictive Control (MPC).

Methods. In contrast to the common approach, in this work we aim to synthesize the best control sequence in terms of some criterion. We use results derived from the Kuhn-Tucker theorem for control synthesis.

Results. A new class of methods capable of leading linear system’s state to zero (or, in case of noisy environment, to its neighbourhood) and stabilization of cognitive map’s functioning was developed. This new methods are capable of controlling not only stable systems, but also unstable and semi-stable ones, even in presence of random perturbations and with constrained control resource. These methods differ in efficiency of control resource utilization and required computational resources. More efficient methods require more computations. That’s why it is necessary to choose an appropriate method in each particular case.

Conclusions. The developed methods can be used to control both technical and any other kinds of systems represented either as controllable linear systems with multiple inputs and outputs or as controllable cognitive maps.

Keywords: variational method, cognitive map, control synthesis, discrete controllable system, moving horizon, linear system, MPC

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REFERENCES

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4. Den Boom V. T. J. J. Model based predictive control: Status and perspective. In Symposium on Control, Optimization and Supervision, CESA’96 IMACS Multiconference. Lille, 1996. pp. 1-12.

5. Rawlings J.B., Mayne D.Q. Model Predictive Control: Theory and Design. Nob Hill Publishing, Madison, WI, 2009, ISBN 978-0-9759377-0-9. 576 p.

6. Richalet, J., Rault A., Testud J.L., Papon J. Model predictive heuristic control: Application to industrial processes. Automatica. 1978, no. 14, pp. 413-428.
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7. Qin S.J., Badgwell T.A. An overview of industrial model predictive control technology. In Kantor Y.C., Garcia C.E. Carnahan (Eds) Chemical Process Control-Assessment and New Directions for Research AIChE Symposium series. Vol. 93, no. 316, pp. 232-256.

8. Gubarev V.F., Mishchenko M.D., Snizhko B.M. (Kondratenko Y., Chikrii A., Gubarev V., Kacprzyk J. (eds)). Model Predictive Control for Discrete MIMO Linear Systems. Advanced Control Techniques in Complex Engineering Systems: Theory and Applications. Studies in Systems, Decision and Control. 2019, Vol. 203.
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9. Gubarev V.F., Shevchenko V.M., Zhykov A.O., Gummel A.V. State estimation for Systems Subjected to Bounded Uncertainty using Mooing Horizon Approach. In Preprints of the 15th IFAC Symposium on System Identification, Saint-Malo, France, July 6-8, 2009, pp. 910-915.
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Received 27.11.2019

Issue 1 (199), article 2

DOI:https://doi.org/10.15407/kvt199.01.019

Cybernetics and Computer Engineering, 2020, 1(199)

BILOSHYTSKA O.K., Senior Lecturer,
Department of Biomedical Engineering,
e-mail: o.k.biloshytska@gmail.com

NASTENKO Ie.A., DSc (Biology), Senior Researcher
Head of the Biomedical Cybernetics Department
e-mail: nastenko.e@gmail.com

PAVLOV V.A., PhD (Engineering), Associate Professor
Associate Professor of the Biomedical Cybernetics Department
e-mail: pavlov.vladimir264@gmail.com

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

THE USE OF COMPLEXITY AND VARIABILITY CHARACTERISTICS FOR THE ANALYSIS OF COMPLEX DYNAMIC SYSTEMS

Introduction. The normal dynamics of a healthy organism is chaotic and the observed “chaos” is inherent in the very nature of the dynamic processes taking place in the organism and the degree of chaotic of these processes may vary in case of pathology in one direction or another. The electrical activity of the brain is also characterized by signs of deterministic chaos, and changes in parameters of its nonlinear dynamics testify to the characteristic changes in brain functioning. The problem of diagnostics and identification of the moment preceding an epileptic seizure or other periods of brain functioning in epileptic patients is not only a problem of choosing a classification method but also of determining quantitative estimates of dynamics reflecting the complexity and variability of the Electroencephalography (EEG) signal.

The purpose of the paper is to form an effective ensemble of features from the characteristics reflecting the complexity and variability of the EEG sig signal ,to construct the prognostic models for the course of epilepsy and to develop the information technology to support diagnostic decision-making based on them.

Methods. The methods of mathematical statistics for the processing of diagnostic information, the methods of mathematical modeling (stepwise logistic regression) — for the construction of prognostic models for estimating the course of epilepsy were used; methodological bases for the creation of information technology for the diagnosis of epilepsy according to the EEG.

Results. Changes in indicators such as Hurst Index, fractal dimension, logistic mapping, and algorithmic signal complexity have been investigated. The mathematical models include variables that are calculated from the EEG data and are available during patient observation. As a result of the application of step-by-step algorithms, the most informative features are included in the models. The selected features allow for the most accurate identification of individual periods of epilepsy flow from the EEG data. It has been established that the use of a decision support system increases the reliability of determining the periods of an epileptic seizure (conditional norm, before, during and after an attack) by an average of 6.6% for children and 8% for adults.

Conclusions. The proposed prognostic models allow to obtain additional information about the periods of epileptic seizures and to predict their onset in time.

Keywords: information technology, EEG, epileptic seizures, epilepsy, complexity and variability indicators, predictive models, logistic regression.

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REFERENCES

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2 Unified clinical protocol for primary, emergency, secondary (specialized) and tertiary (highly specialized) epilepsy in children. Kyiv, 2014 (In Ukrainian). URL: http://mtd.dec.gov.ua /images/dodatki/2014_276_Epilepsii/2014_276_YKPMD_epilepsiya_dity.pdf. (Last accessed: 11.09.2019)

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14 Biloshytska O.K., Nastenko Ie.A. Evaluation of prognostic possibilities of EEG signal behavior complexity indicators in epileptic seizures. Information systems and technologies in medicine (ISM-2018): Collection of scientific papers of the I International scientific-practical conference (Kharkiv, 28-30th of Nov, 2018), Kharkiv, 2018, pp. 95-97 (In Ukrainian).

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22 Biloshytska O.K. Information technology for estimating the course of epilepsy by indicators of electroencephalogram complexity: PhD thesis: 05.13.09 / International Research and Training Center for Information Technologies and Systems of the National Academy of Science of Ukraine and Ministry of Education and Science of Ukraine, Kyiv, 2019, 183 p. (In Ukrainian).

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Received 27.12.2019

Issue 1 (199), article 1

DOI:https://doi.org/10.15407/kvt199.01.005

Cybernetics and Computer Engineering, 2020, 1(199)

KYYKO V.M., PhD (Engineering),
Senior Researcher of Pattern Recognition Department
e-mail: vkiiko@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

MATCHING BASED MULTISTYLE LICENSE PLATE RECOGNITION

Introduction. A State-of-the-Art of license plate (LP) recognition from images is observed. Despite the fact that License Plate Recognition (LPR) is often regarded as a solved task, country-specific systems are mostly designed that limits their application. Pay attention to the increasing mobility, effective LPR systems must handle multistyle LP including multinational ones that have different fonts and syntax. Another bottleneck of LPR is that accuracy of recognition at varying environmental conditions as well as of low resolution or degraded LP usually is rather low.

The purpose of the paper is to develop algorithms for multistyle single line LP learning and recognition from images as well as for comparatively low resolution LP processing.

Methods. Randomized Hough transform is used for detecting horizontal frame lines and subsequent LP localization in image. Structural feature matching approach is used for
character recognition. Correction of recognition results is based on calculation of modified Levenstein distance (MGED) between LP description and templates.

Results. New algorithms for multinational license plate learning and recognition from images are proposed. Localization of LP in images is based on LP frame detection using a randomized Hough transform to detect horizontal contour frame line segments. Recognition of segmented characters inside LP is based on searching key points in skeletonized character images and matching these points with etalons. Correction of recognition LP output is carried out by matching and defining MGED between LP input description and templates. Online active learning for recognition of new LP symbols and templates is also proposed. Results of testing developed algorithms and software are described.

Conclusions. Algorithms for multistyle LP localization and recognition from images are proposed. Control and correction of recognition results is based on calculation of MGED between input LP description and templates which are more general in comparison conventional text lines. As future work, it is planned to increase accuracy by learning feature etalon weights, as well as to consider other LP types for recognition and to test developed means on more representative date samples.

Keywords: license plate localization and recognition, key points matching, Levenstein distance.

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Received 11.11.2019