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Issue 182, article 8

DOI:https://doi.org/10.15407/kvt182.02.086

Kibern. vyčisl. teh., 2015, Issue 182, pp.

Nastenko I.А., Boyko A.L., Nosovets О.K., Teplyakov K.I., Pavlov V.А.

National Technical University of Ukraine “Kiev Polytechnical Institute” (Kiev)

SYNTHESIS OF LOGISITIC REGRESSION, BASED ON SELF-ORGANISATION PRINCIPLES OF MODELS

Introduction. Requirements for modeling algorithms and their implementations varies depending upon the desired properties of the models, which has to be received in restrictions on the available computational resources. Examples of desired properties — accuracy, efficiency ratings, the lowest sensitivity to a change in the data of the model error, variance estimation of parameters, p values etc. Depending on the specific use of models, those or other criteria are taken as a basis for designing specific algorithm simulation. However, choice of the solution of resulting model is usually left to the user. This article considers the possibility of stepwise regression algorithm’s automatic optimization of parameters that is based on principles of self-organization on an example of the synthesis of the logistic model.
The purpose of this article is the improvment the quality of logistic regression classification models due to automatic optimization multivariate binary logistic regression algorithm parameters.
Results. The essence of the modification of stepwise logistic regression standard algorithm: defines penter , pleave grid for each combination of the thresholds calculates stepwise logistic algorithm and the corresponding value of the external criteria. Proposed external criteria reflects the classification accuracy on the training and test datasets, on the one hand, and the requirement to balance the quality of recognition in each class on the other. The stated procedure is repeated for the next value of the grid parameters of the algorithm. Final evaluation of the model is given in the exam sample data. For logistic model calculation and quality’s comparison of classification between standard logistic regression (glm function in R software) and proposed version of modified stepwise algorithm were taken data obtained in the laboratory of functional diagnostics at Department of Physical Education NTUU “KPI”. The purpose of the example is to get a classifying function, of group of subjects with certain states of the cardiovascular system from the rest of the test sample. Standard algorithm demonstrated on examination sample classification quality — 81%, the area under the ROC — curve — 0.8685. Graphs of sensitivity and specificity, and ROC curve for modified algorithm showed the results: quality of the classification algorithm — 90.5 %, area under the ROC — curve — 0.9717.
Conclusions. Article proposes stepwise logistic regression based on the principles of self-organization synthesis algorithm. In order to optimize the parameters of the algorithm proposed by external criterion, which reflects the classification accuracy on the training and test samples and requirement to balance the quality of recognition in each class the effect was received. For the aboved example the classification of functional states of the cardiovascular system in comparison of the standard stepwise algorithm with the proposed algorithm has shown classification quality improvement on 10 % on examination sample.
Keywords: logistic regression, stepwise regression, self-organization’s principles.

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References

  1. Strighov V., Krimova E., Selection methods of regression models — Moscow: CC RAS — 2010. — 45 p. (in Russian).
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Received 15.06.2015

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Issue 182, article 7

DOI:https://doi.org/10.15407/kvt182.02.084

Kibern. vyčisl. teh., 2015, Issue 182, pp.

Krivova O.A., Kozak L.M.

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 (Kiev)

СOMPLEX ESTIMATION OF REGIONAL DEMOGRAPHIC DEVELOPMENT

Introduction. Several studies are being conducted in the world to measure developmental disparities between countries, regions and territorial units. Composite indicators (or indexes) are used whenever a lot of variables are needed for evaluating developmental disparities between territories. Demographic variables are considered as important indicators of socio-economic development of regions. We show how cluster analysis can be combined with elements of multicriteria decision analysis (MCDA) to construct composite index regional demographic development of Ukraine.
The purpose of this article is the development of regional socioeconomic systems analysis methodology and construction of composite indicators of regional demographic development.
Results. We have used 5 territorial social-demographic indicators: 1) total fertility rate; 2) death rate of children under age of five; 3) life expectation at birth; 4) survivorship probabilities for men from 20 to 65 years; 5) survivorship probabilities for women from 20 to 65 years. The following strategy can be pursued in order to construct composite index . First, a cluster analysis (algorithms Ward and K-means) for defining clusters of regions based on the value of the individual indicators is used. The result of the cluster analysis is typological clusters of the selected regions. Second, such as each cluster can be characterized with a centroid, these centroids must be ordered from best to worst. Weights of composite index are calculated as coefficients of the best linear regression model of preference function.
Conclusion. The composite index of regional demographic development allows to assess the degree of variance in regional demographic development and ranking of regions.
Keywords: clustering, a composite indicator, the index of regional demographic development, ordered classification.

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References

  1. Methods of measuring human development regions of Ukraine; Resolution adopted by the College of the State Statistics Committee of Ukraine and Presidium of NAS of Ukraine 14.03.2001 р. № 76 Available at: http://www.ukrstat.gov.ua/metodod_polog/metod_doc/sp/sp_04.pdf. (in Ukrainian).
  2. Regional statistics. Statistical Yearbook Regional Human Development Available at: https://ukrstat.org/uk/druk/publicat/Arhiv_u/15/Arch_rir_zb.htm. (in Ukrainian).
  3. Libanova E.M. Human development in Ukraine: transformation of the standard of living and regional disproportion — Kyiv: IDSS NANU — 2012. — 436 p. (in Ukrainian).
  4. Porter M. E. Location, competition, and economic development: Local clusters in a global economy // Economic Development Quarterly — 2000. — vol. 14. — №1— pp. 15–34.
  5. Izard W. Methods of Regional Analysis: An Introduction to Regional Science. — M.: Progress — 1960. — 660 p. (in Russian).
  6. Granberg A.G. Fundamentals of regional economy. 4th ed. — M.: GU HSE — 2004. — 495 p. (in Russian).
  7. Libanova E.M. Human development of the regions of Ukraine: assessment methodology and current state — Kyiv. — 2002. — 110 p. (in Ukrainian).
  8. Gerasymchyk Z.V. Regional policy of sustainable development: theory, methodology, practice — Lutsk: LNTU — 2011. — 260 p. (in Ukrainian).
  9. Ayvazian S. A. Integrated indicators of the quality of life of the population: their construction and use in socio-economic governance interregional comparisons — M.: TsEMI RAN — 2000. — 117 p. (in Russian).
  10. Hagerty. M.R., Land K.C. Constructing Summary Indices of Quality of Life A Model for the Effect of Heterogeneous Importance Weights// Sociological Methods Research — 2007. — vol. 35. — № 4. — pp.455–496.
  11. Shishkіn V.S. Conceptual and methodological approaches to regional disparities in human development//Statistics of Ukraine — 2001. — № 1. — pp. 30–38. (in Ukrainian).
  12. Makarova, O.V., Hladun O.M. Regional Human Development Index: Causes and areas of improvement methods of calculation // Statistics of Ukraine — 2012. — № 1. — pp. 10–15. (in Ukrainian).
  13. Grygoruk P.M., Tkachenko I.S. Methods of Integral Index Construction // Business Inform — 2012 — №4. — pp. 34–38. (in Ukrainian).
  14. Makotsoba M.B. Integrated estimation, ranking and clustering regions of Ukraine in terms of progress in human development // Economy and management — 2012. — № 4. — pp. 144–151. (in Ukrainian).
  15. Ohlikh V.V., Yefanova T.I. Regional space: methodical approach to the assessment of intraregional differentiation// Regional economy — 2014. — № 4. — pp. 40–47. (in Ukrainian).
  16. Composite Indicators Research Group Available at: https://compositeindicators.jrc.ec.europa.eu/?q=content/overview
  17. Handbook on constructing composite indicators. Methodology and user guide OECD/JRC. 2008 Available at: http://www.oecd.org/std/42495745.pdf
  18. Freudenberg M. Composite indicators of country performance: a critical assessment — Paris: OECD, STI WORKING PAPER — 2003. — № 16. — 34 p. https://www.itu.int/osg/spu/ni/wsisbridges/linked_docs/Background_papers/otherdocs/OECD_WP_2003_16.pdf
  19. The typology of Russian regions/B. Boots, S. Drobyshevskyi, O. Kochetkova — М.: Gaidar institute for Economic Policy, CEPRA — 2002. — 159 p. (in Russian).
  20. Ignatieva A., Maryev O. Methodical attitude to analyses of regional development stability on the basis of Kohonen’s self-organizing maps//Economy of region, Institute of Economic — Yekaterinburg — 2008. — № 2. — pp. 116–129. (in Russian).
  21. Saisana M., Saltelli A., Tarantola S. Uncertainty and sensitivity analysis techniques as tools for the analysis and validation of composite indicators//Journal of the Royal Statistical Society — Blackwell Publishing — 2005. — vol. 168. — № 2. — pp. 307–323.
  22. Ishizaka A, Nemery P. Multi-criteria decision analysis: methods and software. 1st ed. — Chichester: Wiley — 2013. — 310 p.
  23. Saaty T. Decision Making. The Analytic Hierarchy Process — М.: Radio Sviaz. — 1993. — 278 p. (in Russian).
  24. Mironova N. O. Integration modifications of the analytical hierarchy process for group decision making support systems//Radio Electronics, Computer Science, Control — Zaporizhzhya, National Technical University — 2011. — № 2. — pp. 47–54. (in Russian).
  25. Smet Y.D., Nemery P., Selvara R. An exact algorithm for the multicriteria ordered clustering problem//Omega. — 2012. — vol. 40. — № 6. — pp. 861–896.
  26. Mirkin B. G. Methods of cluster analysis for support decision-making. Review. Preprint WP7/2011/ 03 Available at: http:/ /www.hse. ru/data/2013/ 03/23/1303511006/WP7_2011_03f.pdf. (in Russian).
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  29. Krivova O.A., Kurilo I.A. The regional typology the natural growth of the population of Ukraine: Cluster approach//Cybernetics and Computer Engineering — 2011. — №. 164. — pp. 89–102. (in Russian).

Received 01.06.2015

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Issue 182, article 6

DOI:https://doi.org/10.15407/kvt182.02.066

Kibern. vyčisl. teh., 2015, Issue 182, pp.

Antomonov M.Y.

State Institution “O.N. Marzeev Institute for Hygiene and Medical Ecology
of NAMS of Ukraine” (Kiev)

THE METHOD OF DETERMINATION OF ENVIRONMENTAL FACTORS JOINT IMPACT IN EPIDEMIOLOGICAL STUDIES FOR BINARY DATA

Introduction. Modern approaches for data analysis combine classical methods and focused on their practical application. Sometimes the information is presented in the form of qualitative characteristics that are characterize the contamination of the research object. Such binary variables are easily transformed into a probability (in percent), so the task description of results performed using probability theory.
The purpose of the article is to develop such a common method forcalculation joint action of the factors that would allow to operate with qualitative (binary) information and would use techniques and formulas of probability theory
Results. A careful analysis was carried out for the existing approaches in the medical and environmental studies for calculating the effect of the joint action of the factors. It was evaluated disadvantages of these approaches that implemented in the theory of probability and mathematical statistics. The article proposes an original method of calculating the combined effect of the factors that allows you to work with the information expressed in binary form. The final expression was designed by using approach of formal logic and probability theory.
Conclusions. It is shown that the known methods of probability theory cannot be adequately used to evaluate the combined effect of the factors. The original method of calculating the probability of the joint action of factors that take into account their possible connection is described.
Keywords: qualitative data, binary variables, joint effect of the factors, the probability of independent and interdependent events.

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References

1 Duke V. A. Samoilenko A. P. Data Mining. Training — SPb, 2001. — 368p.

2 David W. Hosmer, Stanley Lemeshow Applied Logistic Regression, 2nd ed. — New York, Chichester, Wiley. 2002. — 383p.

3 Nasledov A. N. SPSS 19: Professional statistical analysis. — SPb, 2011. — 400 p.

4 Greenacre M. Correspondence Analysis in Practice, 2nd ed. — London: Chapman & Hall / CRC — 2007. — 280 p.

5 Ritchie M. D., Hahn L. W., Roodi N., Bailey L. R., Dupont W. D., Parl F. F., Moore J. H. Multifactor-dimensionality reduction reveals high-order interactions among estrogenmetabolism genes in sporadic breast cancer. Am. J. Hum. Genet. 2001 Jul; 69 (1): 138-47. https://doi.org/10.1086/321276

6 Hahn L. W., Ritchie M. D., Moore J. H. Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions//Bioinformatics. 2003 Feb 12; 19 (3): 376-82 https://doi.org/10.1093/bioinformatics/btf869

7 Orlov A. I. Applied Statistics — M .: Publisher “Exam”, 2004. — 656 p.

8 Antomonov M. Y. Mathematical processing and analysis of medical-biological data. — Kiev: Publishing house “Malii Druk”, 2006. — 558p.

9 Gaydyshev I. Analysis and data processing — St. Petersburg, 2001. — 750p.

10 Wentzel E. S. Probability 10th ed., Sr — M.: “Academy”, 2005. — 576 p.

11 Gnedenko B. V., Khinchin A. Y. An elementary introduction to the theory of probability, 1970. — 168p.

12 Novikov P. S. Elements of mathematical logic. 2nd ed. — M .: Nauka, 1973 — 400 p.

Received 02.06.2015

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Issue 182, article 5

DOI:https://doi.org/10.15407/kvt182.02.045

Kibern. vyčisl. teh., 2015, Issue 182, pp.

Aralova N.I.

V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences
of Ukraine (Kiev)

MATHEMATICAL MODEL OF THE SHORT- AND MEDIUM-TERM ADAPTATION OF RESPIRATORY SYSTEM OF THE PERSONS WORKING IN EXTREME CONDITIONS OF HIGH MOUNTAINS

Introduction. In addition to experimental studies in recent years the methods of mathematical modeling of individual functional systems and the whole organism in certain situations are widely used, the results of which complement the system of experimental data and allow to make a more complete assessment of the functional state of the organism.
Purpose. To explore on a mathematical model of the respiratory system the functional mechanisms of adaptation of the respiratory system to the conditions of mountain meteorological factors for persons performing heavy exercise in a hypobaric hypoxia.
Results. The model, that describes transport and mass exchange of respiratory gases in the respiratory tract, the alveolar space, blood and tissues with use of ordinary nonlinear differential equations, for the mathematical analysis of the adaptive capacity of the organism hypoxia of various etiologies is used. The regulation is based on a compromise resolution of conflicts arising between the tissues and organs in the struggle for oxygen in a deficit. On the basis of this model, the models of short time and medium adaptation persons performing heavy physical activity in a midlands are created. Results of simulation experiment are presented.
Conclusion. The article presents a mathematical model of short-term and medium term adaptation FRS for rescuers and the results of the numerical analysis of this model. On this basis, the practical recommendations for the selection of the persons, that are exposed to the combined effects of hypobaric hypoxia and the hypermetabolic hypoxia, are given.
Keywords: short-term adaptation, medium term adaptation, respiration system, hypobaric hypoxia, hypermetabolic hypoxia, reliability, mathematical model of respiratory system.

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References

  1. Onopchuk Yu.N. Homeostasis function of the respiratory system as a result of in-system and system-environment interaction // Bioekomedicine. Unified Information Space — Kiev — 2001. — P.59–81(in Russian)
  2. Onopchuk Y.N., Beloshitsky P.V. Aralova N.I. On the question of reliability of functional systems // Cybernetics and computing tehnics. 1999. — Vol. 122. — P. 72–89 (in Russian)
  3. Polinkevich K.B., Onopchuk Y.N. Conflicts in the regulation of the main function of the respiratory system of the body, and mathematical models of their solution // Cybernetics. — 1986. — № 3. — P. 100–104.
  4. Bіloshitsky P.V. Klyuchko O.M., Onopchuk Y.N. Research results of the problems of adaptation by Ukrainian scientists on Elbrus // Vіsn. NAU. — 2008. — № 1. — P. 102–108.
  5. Onopchuk Y.M., Bіloshitsky P.V. Klyuchko O.M. Creation of mathematical models for the research by Ukrainian scientists on Elbrus. // Vіsn. NAU. — 2008. — № 3. — P. 146–155.

Received 07.09.2015

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Issue 182, article 4

DOI:https://doi.org/10.15407/kvt182.02.034

Kibern. vyčisl. teh., 2015, Issue 182, pp.

Kopets M.M.

National Technical University of Ukraine «Kyiv Polytechnic Institute» (Kiev)

OPTIMAL CONTROL BY VIBRATIONS OF THE BEAM WITH VARIABLE CROSS-SECTION

Introduction. The last half-century is characterized by the rapid development of technology. Significant progress has been made in the rocket, aircraft, shipbuilding and space technology, etc. All sectors have oscillatory processes. In some cases, they can usefully be taken into account to improve the quality of the process, while others, on the contrary, it is necessary to suppress because of their negative impact on the final process. This means that the oscillatory processes must not only be learned, but also be able to manage them effectively. Similar problems effectively manage mechanical processes just studying optimal control theory. The purpose of this article is to study the linear-quadratic problem of optimal control by oscillations of the beam with variable cross-section in the case of the free ends of the beam.
Statement of the Problem. The state equation is linear partial differential equation of the fourth order of hyperbolic type with given initial conditions and homogeneous boundary conditions. Quality of the process is estimated by quadratic functional. The admissible control is such a function which belongs to the class of square Lebesgue integrable functions. Optimal control is admissible control which is implemented at least the cost functional.
The purpose of the paper is to determine the necessary conditions for optimal control of process vibrations of a beam of variable cross-section in the case of the free ends of the beam and to give solution of integral-differential Riccati equations for the optimal control.
The main results. Necessary optimality conditions for the considered optimization problem are obtained. Analysis of these conditions made it possible to bring the system of integro-differential Riccati equations with partial derivatives. The solution of this system is used in the construction of an explicit formula for the calculation of optimal control.
Conclusions. The article investigates the linear-quadratic optimal control process vibrations of a beam of variable cross-section in the case of the free ends of the beam. Necessary optimality conditions for the considered optimization problem are obtained. Analysis of these conditions made it possible to bring the system of integro-differential Riccati equations with partial derivatives. The solution of this system is used in the construction of an explicit formula for the calculation of optimal control. Further development of the obtained results is to study the case where the control time tends to infinity. In the theory of optimal control, this problem is called the problem of analytical construction of the regulator.
Keywords: linear quadratic optimal control problem, method of Lagrange multipliers, necessary optimality conditions, oscillations of the beam, partial derivatives, system of integro-differential equations.

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References

  1. Bublik B.N., Kirichenko N.F. Fundamentals of control theory. — K .: Higher School — 1975. — 328 p.
  2. Naidu D.S. Optimal control systems // Electrical engineering textbook series. — CRC PRESS — Boka Raton London — New York — Washington, D. C. — 2003. — 433 p.
  3. Bodner V.A. Theory of automatic flight control. — M .: Nauka — 1964. — 700 p.
  4. Kopets M.M. Optimal control of vibrations of a rectangular membrane // Cybernetics and computer engineering. — 2014. — Vol. 177. — P. 28–42.

Received 10.07.2015

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Issue 182, article 3

DOI:https://doi.org/10.15407/kvt182.02.025

Kibern. vyčisl. teh., 2015, Issue 182, pp.

Pavlov A.V.

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

APPROACH TO ORGANOZATION OF RECURRENTAND-PARALLEL COMPUTATIONS IN AUTOMIZED STRUCTURE-PARAMETRIC IDENTIFICATION SYSTEM

Introduction. Development and optimization of methods and algorithms for solving statistical modeling problems are the basic directions in science undoubtedly. Although even the most efficient methods and technologies lose their value if they stay just program modules which can be used only by programmers. To be used in practice they should be integrated in some software that has intuitive user-friendly interface. Such software helps to discover a real value of the methods behind it.
The purpose of the paper is increasing the usage effectiveness of а recurrentand-parallel iterative algorithm by developing a full-fledged modern software based on it for solving forecasting, extrapolation and approximation problems.
Results. The main task of integration of GUI and computational module is a union of two mechanisms of parallization: Threading Building Blocks (TBB) parallization and Qt-parallization. The main idea of proposed approach is that every operation (including the model building operation that create own TBB-threads) initiated by a user should perform in additional Qt-thread. A design pattern that solve this task was developed. The pattern was used to finally implement the ASIS. The system applied to forecast investments security of Ukraine. A system of forecasting models that describe the state of Ukrainian investments security was build. Mean absolute percentage error of the models hit the [-7; +7] interval on independent dataset, that indicate a good forecasting ability of the models.
Conclusion. The work suggests an approach to organization of recurrent-andparallel computations in ASIS that allow integrating the most effective methods for solving statistical modeling problems in user-friendly intuitive full-fledge system that allows any user to solve forecasting, regression and approximation problems with high efficiency. The system was applied to forecast Ukrainian investments security. The economic interpretation of the obtained forecasts says that in 2013 year Ukraine will gain more investments from abroad than from inner investors Ukrainian manufacturing will increase rates; on the background rise of overall country investments, the investments in basic capital will decline.
Keywords: Multithreaded parallelization, design patterns, group method of data handling, recurrent-and-parallel computations, Qt, TBB.

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References

  1. Efimenko S., Stepashko V. S, Basics of recurrent-and-parallel computations in combinatorial algorithm COMBI of GMDH // Controll sysmems and machines — 2014. — № 6. — P. 27–33. (in Russian)
  2. Efimenko S.M. Combinatorial algorithm of GMDH with sequential complication of structures based on recurrent-and-parallel computations // Inductive modeling of complex systems — Vol. 6. — 2014. — P. 81–89. (in Ukrainian)
  3. Pavlov A.V. Parallel relaxational iterative algorithm of GMDH // Inductive modeling of complex systems — Vol. 6. — 2014. — P. 33–40.
  4. Pavlov A.V. Design of automated structure-parametric identification system // Inductive modeling of complex systems — Vol.7— 2015. — P. 33–40.
  5. Internet resource https://ru.wikipedia.org/wiki/Qt.

Received 28.10.2015

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Issue 182, article 2

DOI:https://doi.org/10.15407/kvt182.02.015

Kibern. vyčisl. teh., 2015, Issue 182, pp.

Balovsyak S.V.1, Fodchuk I.M.1, Solovay Yu.M.2, Lutsyk Ia.V.1

1Yuriy Fedkovych Chernivtsi National University (Chernovtsy)

2Bukovinian State Medical University (Chernovtsy)

MULTILEVEL METHOD OF LOCAL CONTRAST INCREASE AND IMAGES HETEROGENEOUS BACKGROUND REMOVAL

Introduction. The increase of local contrast and removal of heterogeneous background are the widespread problems of the digital image processing [1–4]. In existing local methods, such as the method of images adaptive contrast enhancement, a value of the local contrast is computed in vicinity of each pixel within a predetermined sliding window. The disadvantages of the existing local methods include poor performance, complicated selection of filter parameters and errors in the calculation of the intensity of the resulting image.
The purpose of the paper is to develop a multilevel method of local contrast increasing and removal of heterogeneous background of images with the high performance and accuracy using the minimal number of filter parameters.
Methods. The signal envelopes are calculated by linear and cubic approximation.
Results. The multilevel method of removing heterogeneous background and local contrast enhancement of images within the window of the Mw Ч Nw pixels size has been elaborated and developed in the MATLAB system [5]. By means of the developed method the heterogeneous background has been successfully removed and local contrast has been increased for the test simulated and medical X-ray images.
Conclusions. Time of the image processing by the multilevel method is shortened comparing with per pixel processing in tR ~ (Mw Ч Nw)2 time, for example at the window size of Mw Ч Nw = 11 Ч 11 pixels the value of tR ≈ 10 times. The optimal distance between the windows centres on height and width is equal to SH0 = [Mw/2] + 1 and SW0 = [Nw/2] + 1, respectively.

Keywords: digital image processing, local contrast increasing, heterogeneous background removal.

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References

  1. Gonzalez R., Woods R., Eddins S. Digital image processing. — M.: Technosphere, 2005. — 1072 p. (in Russian)
  2. Russ J.C. The image processing handbook. 6th ed. — CRC Press, 2011. — 817 p.
  3. Design features of medical information decision support system based on data mining / G.V. Knyshov, A.V. Rudenko, E.A. Nastenko & others // Cybernetics and Computer Engineering. — 2014. — Vol. 177. — P. 79–87. (in Russian)
  4. Bondina N.N., Muratov R.Yu. Adaptive filtering and image contrast changing algorithms // Vestnik NTU “KPI”, 2014. — №35. — P.35–42. (in Russian)
  5. Ketkov Y.L., Ketkov A.J., Schulz M. Matlab 7: programming, numerical methods. — SPb. : BHV-Petersburg, 2005. — 752 p. (in Russian)

Received 20.10.2015

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Issue 182, article 1

DOI:https://doi.org/10.15407/kvt182.02.004

Kibern. vyčisl. teh., 2015, Issue 182, pp.

Surovtsev I.V.

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

THE METHOD OF DIGITAL FILTERING OF ELECTROCHEMICAL SIGNALS IN THE CHRONOPOTENTIOMETRY

Introduction. It is important to use methods of digital filtration of signals, that do not distort the form of signal and use its internal characteristics, such as points of extrema for systems of measuring the concentration of toxic elements in chronopotentiometry.
The purpose of research is to create a method digital filtering by using extrema points for performing high-frequency treatment of different types of electrochemical signals while maintaining the shape of the useful signal which increases monotonically.
Methods. The method of digital filtering is based on using of the method of determining the spectrum of the analog signal by points of extrema.
Results. Created method of high-frequency filtration of electrochemical signals has reduced errors in determining the concentration, since it does not distort the form of the useful signal and does not lead to a blurring of the boundaries of the components of measurement of elements. The method is actively used in existing devices measuring the concentration toxic elements in the systems of dynamic axle-by-axle weighting of automobiles and continuous dosing, as well as in many other technical systems of measurement.
Conclusion. The proposed method of digital filtering has substantially universal character and can be used for preliminary digital processing of very different physical or chemical signals.
Keywords: digital filtering, extrema points of signal, chronopotentiometry.

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References

  1. Surovtsev I.V., Galimov S.K., Martynov I.A., Babak O.V., Galimova V.M. Device for measurement of concentration of toxic elements. Patent 107412 Ukraine, Int.C1. (2006) G01N 27/48, 2014 (in Ukrainian).
  2. Surovtsev I.V., Tatarinov A.E., Galimov S.K. The modeling of the Differential Chronopotentiograms by the Sum of Normal Distributions//Control System and Computers — 2009. — №. 5. — pp.40–45 (in Russian).
  3. Oppenheim A.V., Schafer R.W. Discrete-Time Signal Processing — NJ: Prentige-Hall, 1999. — 860 p.
  4. Fainzilberg L.S. Information technologies of signal processing complex form. Theory and practice — Kiev: Naukova dumka, 2008 — 333 p. (in Russian).
  5. Zadiraka V.K., Melnikova S.S. Digital signal processing — Kiev: Naukova dumka, 1993. — 294 p. (in Russian).
  6. Shelevitsky І.V., Shutko M.O., Shutko V.M., Kolganova O.O. Splines in digital data processing and signals — Kryvyy Rih: Vydavnychyy dim, 2008. — 232 p. (in Ukrainian).
  7. Skurykhin V.I., Ponomareva I.D., Siverskij P.M., Tsepkov G.V. Method of determining the spectrum of the analogue signal. Patent 845600 SSSR, 1981 (in Russian).
  8. Tsepkov G.V. Methods of data compression for quick spectrum and correlation transformations//Visnyk Shidnoukrains’kogo nacional’nogo universytetu im. V.Dalja — 2013. — № 15 (204). — pp. 222–229 (in Russian).
  9. Surovtsev I.V., Martynov I.A., Galimova V.M., Babak O.V. Device for measurement of concentration of heavy metals. Patent 96375 Ukraine, Int.C1. (2006) G01N 27/48, 2011 (in Ukrainian).
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Received 06.07.2015