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IEEE Ukraine Section

IEEE Ukraine Section (West) MTT/ED/AP/EP/SSC Societies

Joint Chapter

Lviv Polytechnic National University, UKRAINE

Lodz University of Technology, POLAND

2019 15th International Conference on the

Experience of Designing and Application

of CAD Systems (CADSM)

CONFERENCE PROCEEDINGS

Polyana (Svalyava), UKRAINE

February 26 – March 2, 2019

Organized by:

IEEE Ukraine Section;

IEEE Ukraine Section (West)

MTT/ED/AP/EP/SSC Societies Joint Chapter

Department of Computer-Aided Design

Institute of Computer Science and Information

Technologies,

Lviv Polytechnic National University

Department of Microelectronics and

Computer Science

Lodz University of Technology

2019 15th International Conference on the Experience of Designing and

Application of CAD Systems (CADSM)

PROCEEDINGS

Part Number: CFP19508-USB

ISBN: 978-1-7281-0053-1

Copyright and Reprint Permission: Abstracting is permitted with credit to the

source. Libraries are permitted to photocopy beyond the limit of U.S. copyright

law for private use of patrons those articles in this volume that carry a code at

the bottom of the first page, provided the per-copy fee indicated in the code is

paid through Copyright Clearance Center, 222 Rosewood Drive, Danvers,

MA01923. For reprint or republication permission, email to IEEE Copyrights

Manager at [email protected].

All rights reserved. Copyright ©2019 by IEEE.

CADSM-2019 ORGANIZING COMMITTEE

Chairman: Prof. Mykhaylo Lobur, Head of CAD Department, Lviv Polytechnic National

University, Ukraine

Vice-chairman: Prof. Andrzej Napieralski, Lodz University of Technology, Poland

Prof. Mykhaylo Andriychuk, CAD Department of Lviv Polytechnic National University,

Ukraine

Conference

Secretary:

Dr. Nazariy Andrushchak,

CAD Department of Lviv Polytechnic National University,

Ukraine

Publication Chair: Prof. Pavlo Tymoshchuk


Ukraine

Financial Chair: Dr. Natalia Bokla


Ukraine

MEMBERS OF ORGANIZING COMMITTEE

Prof. Pavlo Tymoshchuk Lviv Polytechnic National University, Ukraine

Prof. Sergiy Shcherbovskyh Lviv Polytechnic National University, Ukraine

Dr. Mykhaylo Melnyk Lviv Polytechnic National University, Ukraine

Dr. Uliana Marikutsa Lviv Polytechnic National University, Ukraine

Dr. Igor Farmaga Lviv Polytechnic National University, Ukraine

Dr. Natalia Bokla Lviv Polytechnic National University, Ukraine

Dr. Wojciech Zabierowski Lodz University of Technology, Poland

Dr. Lukasz Starzak Lodz University of Technology, Poland

Dr. Jacek Nazdrowicz Lodz University of Technology, Poland

Jan Napieralski Lodz University of Technology, Poland

Andriy Pavlyuk Lviv Polytechnic National University, Ukraine

Vitaliy Yaremko Lviv Polytechnic National University, Ukraine

INTERNATIONAL PROGRAM COMMITTEE

Prof. Andriychuk M. IEEE Ukraine Section (West) MTT/ED/AP/EP/SSC Societies

Joint Chapter (Vice-chairman)

Prof. Dziuban J. Wroclaw University of Technology, POLAND

Prof. Fedasyuk D. Lviv Polytechnic National University, UKRAINE

Prof. Georgiev G. University of Veliko Turnovo, BULGARIA

Prof. Hahanov V. Kharkov National University of Radio Electronics, UKRAINE

Prof. Janicki M. Lodz University of Technology, POLAND

Prof. Klymash M. Lviv Polytechnic National University, UKRAINE

Prof. Kuzmicz W. Warsaw University of Technology, POLAND

Prof. Levin B. Holon Institute of Technology, ISRAEL

Prof. Lobur M. Lviv Polytechnic National University, UKRAINE (Chairman)

Prof. Makowski D. Lodz University of Technology, POLAND

Prof. Matviykiv O. Lviv Polytechnic National University, UKRAINE

Prof. Melnyk A. Lviv Polytechnic National University, UKRAINE

Prof. Napieralski A. Lodz University of Technology, POLAND (Vice-chairman)

Prof. Pavlysh V. Lviv Polytechnic National University, UKRAINE

Prof. Pleskacz W. Warsaw University of Technology, POLAND

Prof. Prudyus Iv. Lviv Polytechnic National University, UKRAINE

Prof. Raida Z. Brno University of Technology, CZECH REPUBLIC

Prof. Rangelow I. Technische Universität Ilmenau, GERMANY

Prof. Sankowski D. Lodz University of Technology, POLAND

Prof. Skryshevsky V. Kyiv National Taras Shevchenko University, UKRAINE

Prof. Tavzarashvili K. University of Georgia, GEORGIA

Prof. Teslyuk V. Lviv Polytechnic National University, UKRAINE

Prof. Yanovsky F. National Aviation University, UKRAINE

Prof. Yashchyshyn Ye. Warsaw University of Technology, POLAND

7/1

978-1-7281-0053-1/19/$31.00 ©2019 IEEE

Computer Aided System of Time Series Analysis

Methods for Forecasting the Epidemics Outbreaks

Yulia Polyvianna

Epidemiology department

Kharkiv National Medical University

Kharkiv, Ukraine [email protected]

Dmytro Chumachenko

Mathematical Modeling and Artificial

Intelligence department

National Aerospace University

“Kharkiv Aviation Institute”


Tetyana Chumachenko

Epidemiology department

Kharkiv National Medical University


Abstract— The research is devoted to the problem of

predicting the incidence of gastroenterocollitis. The paper

discusses the forecasting of time series by statistical models.

The methods of exponential smoothing and adaptive

exponential smoothing are proposed, applied to additive and

multiplicative time series models. The analysis of the results

obtained using the developed computer aided system.

Keywords—forecasting of time series, forecasting the

epidemic process, method of exponential smoothing, Brown

polynomial model, adaptive Holt method

I. INTRODUCTION

Epidemiological surveillance of infectious diseases and the prevention of outbreaks of certain infectious diseases is an important task of ensuring safety in the field of public health, because the occurrence of outbreaks of infection and the worsening of the epidemic situation create problems for national health services, increase financial costs, etc [1]. If you do not prevent the occurrence of outbreaks and the worsening of the epidemic situation, infections can quickly spread to other territories, causing significant medical, social and economic damage. Among current infections of modern times, foodborne diseases play a significant role, the incidence of which tends to increase in both developed and developing countries, this problem is rapidly becoming a global one. Public health is faced with the task of reducing the impact of these infectious diseases on the health and socio-economic well-being of people.

This problem requires solving the task of processing and analyzing information obtained in the course of the activity of the sanitary-epidemiological service. This is a time-consuming task that modern information technologies can facilitate.

This research is based on official data on gastroenterocolitis (GEC) cases monthly reported in Kharkiv Oblast (East Ukraine) during 2013-2017 without detection of etiological agent of infection.

GES is a total lesion of the human gastrointestinal tract (small and large intestine, as well as the stomach). Acute gastroenterocolitis, as a rule, caused by infectious agent, develops as a result of food toxicoinfections that occur when pathogenic microorganisms (bacteria, viruses, protozoa) and / or their toxins enter the body with food or water; symptoms

of intoxication, vomiting, diarrhea. In the scientific literature can be found the terms "Gastroenteritis" (if the process does not involve the large intestine), "infectious diarrhoea", "acute intestinal infections", "acute diarrhoeal infection". Using data without decoding the type of pathogen that caused gastroenterocolitis, according to the preliminary diagnosis, without waiting for the results of laboratory tests, it is possible to determine in time the onset of complications of the epidemic situation and to take adequate restraining measures in time. [2]

To solve the problem, we consider it as a forecasting problem based on time series. In work [3] the factors are described, to which influence a time series is subject and four components are allocated:

a trend that represents a non-periodic change in the average over the time interval on which the time series is determined;

seasonal factor that determines the actions that are repeated in units of days, weeks, months, years;

cyclical factors affecting the series;

random factor.

In paper [4], time series models are considered: additive and multiplicative, which represent the dependence of factors. Knowing the essence of the phenomenon or process described by the time series, it will not be difficult to choose the appropriate model.

To predict epidemic processes, there are many complex methods that are characterized by the possibility of taking into account a large number of factors affecting the dynamics of the incidence of diseases, heterogeneity of the population and territories, and so on. Among such methods one can single out methods based on neural networks [5, 6] and multi-agent simulation [7, 8].

However, given the nature of the data that is collected on the incidence of GEC in Ukraine, we consider statistical time-based adaptive statistical forecasting methods, such as the exponential smoothing method, Holt method and Brown method. The considered methods have a number of properties [9]:

Applicability for a wide range of tasks.

7/2

Forecasting is based on intensive analysis of information contained in individual time series.

It does not require a large amount of information.

Clarity and simplicity of the mathematical formulation.

II. METHODS

The first task of investigation of the time series is to test the hypothesis of a trend. With the help of the Foster-Stewart method [10] the presence of a trend of GEC morbidity was established, a non-random component was identified. Visual analysis showed that, as a non-random component in the analyzed time series, it makes sense to distinguish between the trend and the seasonal component. To simulate the trend of time series, the moving average method was used [11]:

1/5 (Un-2 + Un-1 + Un + Un+1 + Un+2) = 1/5 Un;

where Un is operator, which characterize the process of summing of five terms of the series.

In the modeling of seasonal variations, the values of the seasonal component were calculated.

To implement the forecast of GEC morbidity, three methods were used: the method of exponential smoothing, the Brown polynomial model, and the adaptive Holt method.

A. Method of exponential smoothing

The peculiarity of the method of exponential smoothing is that in the procedure for equalizing each observation only the values of the previous levels of a series of dynamics taken with a certain weight are used [12]. This method is recommended for short-term forecasting, for stationary data, or when there is a slow growth in data or, conversely, a decrease in time.

The exponential smoothing of the series is carried out by the recurrence formula:

Ft = αXt + βFt-1, m

x

F

m

i

i 1

0,

where Ft is value of exponential average at time moment t; Xt is an element of time series, X = {x1, x2, …}; α is smoothing parameter, 0 < α < 1; β = 1 – α.

The constant α affects the accuracy of the forecast. It should also provide a minimum of forecast error. If the data has significant fluctuations or randomness, a small value should be used for α. On the other hand, data with little randomness or a clear model should use a larger value for α.

B. Brown polynomial model

The difference between a single exponential smoothing and a Brown polynomial model is the presence of additional formulas for estimating the trend, so they can be used to predict non-stationary time series [13].

The following formulas are used in a second-order adaptive polynomial model:

St’ = αXt + (1 – α)St-1

’;

St’’ = αSt

’ + (1 – α)St-1

’’;

St’’’

= αSt’’ + (1 – α)St-1

’’’,

where St’, St

’’, St

’’’ are exponential average of first, second

and third order.

Initial conditions:

S0’ = αt – βbt/α + βct(2 – α)/2α

2;

S0’’ = αt – 2βbt/α + βct(3 – 2α)/ α

2;

S0’’’

= αt – 3βbt / α + 3βct(4 – 3α) / 2α2.

Coefficients estimation:

bt = α / 2β2[(6 – 5α)St

’ – (10 – 8α)St

’’ + (4 – 3α)St

’’’;

at = 3St’ – 3St

’’ + St-1

’’’;

ct = α / β2[St

’ – 2St

’’ + St-1

’’’].

The forecast for m steps forward is written by a simple quadratic polynomial:

Ft+m = at + btm + ctm2 / 2.

C. Adaptive Holt method

The three-parameter exponential smoothing model of Holt is similar to the Brown model [14], since it estimates the trend and uses it in forecasting. Equations are written in following form:

St = αXt + (1 – α)(St-1 + Tt-1 + Rt-1 / 2);

Tt = βdSt + (1 – β)Tt-1;

Rt = γd2St + (1 – γ)Rt-1,

where dSt = St – St-1, d2St = dSt – dSt-1.

The forecasting formula can be written as:

Ft+m = St + Tt m + Rt m2 / 2,

7/3

where m is number of forecasting steps.

After a few modifications, we present a model that takes into account the trend and seasonality. Adaptive Holt method takes into account these factors and is analytically recorded as:

Tt = C (Xt’ – Xt-1

’) + (1 + C) Tt-1;

St = B (Xt / Xt’) + (1 – B) St-L;

Xt’ = A (Xt / St-L) + (1 – A) (Xt-1

’ – Tt-1),

where Tt is trend from time factor, St is seasonal factor, L is period of seasonal cycle, Xt

’ is smoothed series.

The scheme of making a forecast for h steps in accordance with the adaptive Holt method is as follows:

Xn’(h) = (Xn

’ + hTn) Sn-L+h, h = 1, 2, …, L;

Xn’(h) = (Xn

’ + hTn) Sn-2L+h, h = L + 1, L + 2, …, 2L.

Adaptive Holt model suggests an additive trend and multiplicative factors, but can be modified to work with a multiplicative trend and an additive seasonal component.

Before forecasting results can be obtained, the accuracy of the forecast must be determined. To do this, you can use the formula for calculating the relative error of predicted values:

εt = (|x’(t) – x(t)| / x(t)) 100%,

where x’(t) is forecasted value, x(t) is actual value ща time

series.

III. RESULTS

The described methods were tested on GEC incidence rates. The forecast was carried out for the October, November and December of 2017.

To automate the prediction of the incidence of GEC using C # programming language, a software package has been developed that allows calculating prognosis morbidity based on existing statistical data. The basic configuration of the software package includes data from 2013 to 2017 years. The data for the years include absolute morbidity by GEC.

Figure 1 shows number of cases of GEC and the process of predicting these indicators using the exponential smoothing method.

Fig. 1. Forecasting the morbidity by GEC using method of exponential

smoothing

Figure 2 shows the dynamics of actual incidence rates and the process of predicting these indicators using the Brown polynomial model.

Fig. 2. Forecasting the morbidity by GEC using Brown polynomial model

Figure 3 shows number of cases of GEC and the process of predicting these indicators using the adaptive Holt method.

Fig. 3. Forecasting the morbidity by GEC using adaptive Holt method

A comparative analysis of the results obtained using the three methods showed that the best result is shown by the Brown polynomial model, and the worst by adaptive Holt method (fig. 4, table 1).

7/4

Fig. 4. Comprehensive analysis of forecasting the morbidity by GEC

using method of exponential smoothing, Brown polynomial model and adaptive Holt method.

TABLE I. NUMERICAL RESULTS OF FORECASTING THE MORBIDITY BY

GEC USING METHOD OF EXPONENTIAL SMOOTHING, BROWN POLYNOMIAL

MODEL AND ADAPTIVE HOLT METHOD.

Number

of month

Real data Forecast

Exponential

smoothing Holt method

Brown

model

58 508 523,012 537,86 510,18

59 401 437,604 496,514 404,53

60 343 371,381 441,572 344,99

The accuracy of the methods depends on the smoothing parameters. The prediction results showed that the accuracy of the predictions is higher with small values of smoothing constants.

Further stages of work are:

obtaining a long-term forecast by statistical methods;

building a forecast using neural network and fuzzy methods;

comparison of the results obtained by neural network, fuzzy and statistical methods on real data provided by the Kharkov Regional Laboratory Center;

implementation of a forecasting information system that allows using the web interface and calculating the forecast in real time.

IV. CONCLUSIONS

Within this study were analyzed data on the incidence rate of GEC cases in Kharkiv Oblast. Factors influencing the time series were considered: the trend, the seasonal component. The obtained results showed that the reliability of the short-term prognosis of the incidence rate of GEC cases in Kharkiv Oblast by the polynomial Brown model shows the best result. The accuracy of the methods depends on the smoothing parameters. The results of the forecast revealed that the accuracy of the forecasts is higher for small values of smoothing constants.

For further research, it is planned to implement a computer aided system as a web application in order to implement the input of data on the GEC incidence in real time, as well as the real time calculation of the predicted incidence. For this purpose it is planned to use the approaches described in paper [15]. The implementation of a computer aided system that allows calculation of the forecast in real time will increase the efficiency of decision-making on the implementation of preventive measures about decreasing GEC incidence by epidemiologists. To optimize the forecasting processes and practical use the developed model can be included in computer aided system of epidemiological surveillance of infectious diseases

REFERENCES

[1] N. Dotsenko, D. Chumachenko, I. Chumachenko “Modeling of the processes of steakholder involvement in commant management in a multi-project environment” 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT), Lviv, 2018, pp. 29-32.

[2] WHO estimates of the global burden of foodborne diseases: foodborne disease burden epidemiology reference group 2007-2015. I.World Health Organization. ISBN 978 92 4 156516 5 World Health Organization, 2015 – 255 p.

[3] H. Wang, C. W. Tian, W. M. Wang, X. M. Luo “Time-series analysis of tuberculosis from 2005 to 2017 in China”, Epidemiology and infection, vol. 146, iss. 8, 2018, pp. 935-939.

[4] L. Zhou “Time series model for forecasting the number of new admission inpatioents”, BMC Medical Informatics and Decision Making, vol. 18, 2018, pp. 18-39.

[5] V.P. Mashtalir, S.V. Yakovlev “Point-set methods of clusterization of standard information”, Cybernetics and Systems Analysis, vol. 37, №3, 2001, pp. 295-307.

[6] V.P. Mashtalir, V.V. Shlyakhov, S.V. Yakovlev “Group structures on quotient sets in classification problems”, Cybernetics and Systems Analysis, vol. 50, №4, 2014, pp. 507-518.

[7] D. Chumachenko et al. “On agent-based approach to influenza and acute respiratory virus infection simulation”, 14th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, TCSET 2018. Proceedings, 2018-April, pp. 192-195.

[8] D. Chumachenko “On Intelligent Multiagent Approach to Viral Hepatitis B Epidemic Processes Simulation”, Proceedings of the 2018 IEEE 2nd International Conference on Data Stream Mining and Processing, DSMP 2018, 2018, pp. 415-419.

[9] K. Bazilevych et al. “Stochastic modelling of cash flow for personal insurance fund using the cloud data storage”, International Journal of Computing, vol. 17, iss. 3, 2018, pp. 153-162.

[10] L. Doucette “ Quantitative Methods and Inferential Statistics: Capacity and Development for Librarians” Evidence Based Library and Information Practice, vol. 12, iss. 2, 2017, pp. 53-58.

[11] D. Alajbeg, Z. Bubas, D. Vasic “Proce distance to moving avegares and subsequent returns”, International Journal of Economics, Commerce and Management, vol. 5, iss. 12, 2017, pp. 33-47.

[12] B. Siregar et al “Comparison of Exponential Smoothing Methods in Forecasting Palm Oil Real Production”, J. Phys.: Conf. Ser. 801 012004, 2017.

[13] O.Yu. Sokolov, O.S. Radivonenko, T.V. Korchak “Methods of analysis of time series in tasks on infectious diseases epidemics outbreaks tasks”, Radioelectronic and computer systems, vol. 2 (21), 2007, pp. 36 – 40.

[14] A. Laouafi et al. “Online electricity demand forecasting based on an effective forecast combination methodology”, Electric Power Systems Research, vol. 148, 2017, pp. 35-47.

[15] M. Mazorchuck, V. Dobriak, D. Chumachenko “Web-Application Development for Tasks of Prediction in Medical Domain”, 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT), Lviv, 2018, pp. 5-8.

vi

CADSM 2019, February 26 – March 2, 2019, Polyana-Svalyava (Zakarpattya), UKRAINE

TABLE OF CONTENT

PLENARY SESSION

Design and Analysis of Lab-Chip Module for Rainwater Chemical Hazards

Monitoring System Oleh Matviykiv, Tamara Klymkovych, Nataliia Bokla, Ihor Farmaha

and Krzysztof Pytel p/1 Intelligent Spectrum Management in 5G Mobile Networks Based on Recurrent

Neural Networks

Taras Maksymyuk, Longzhe Han, Stanislav Larionov, Bohdan Shubyn,

Andriy Luntovskyy and Mykhailo Klymash p/5

Signal Processing Algorithm for Active Aperture Synthesis Systems Vladimir Pavlikov, Valeriy Volosyuk, Simeon Zhyla, Huu Nguen Van,

Kiem Nguen Van and Anton Sobkolov p/9

CAD MODERN INFORMATION TECHNOLOGY

Set-Theoretical FSM Models Activity Subsystem for Cognitive Control Systems

Mykhailo Poliakov, Oleksii Poliakov and Sergey Subbotin 1/1

Optimization of the Structural Characteristics of the Robotic System Holder

Andriy Zdobytskyi, Mykhailo Lobur and Vasul Breznitskyi 1/5

Designing A Generator of Random Electronic Message Based on Chaotic Algorithm

Iryna Artyshchuk, Olexander Belej and Natalia Nestor 1/9

Development of CAD/CAM/CAE Systems of Designing Spatial Frame for

Technological and Machine-Tool Equipment

Yuriy Rozov, Serhii Rusanov, Hanna Rudakova, Dmytro Dmitriev,

Anton Omelchuk and Dmytro Fedorchuk 1/14

The Analysis of the Optimal Data Distribution Method at the Content Delivery

Network

Nazar Pleskanka, Maryan Kyryk and Mariana Pleskanka 1/20

Development the Software for Simulation of Physical Fields in Wood Drying

Chambers by Using Cellular Automata

Yaroslav Sokolovskyy, Oleksiy Sinkevych and Roman Voliansky 1/24

Mathematical Models and Analysis of the Heat-Mass-Transfer in Anisotropic

Materials Taking Into Account the Boundaries of Phase Transition

Yaroslav Sokolovskyy, Iryna Boretska, Bogdana Gayvas and Igor Kroshnyy 1/28

Hardware Implementation of Sigmoid Activation Functions Using FPGA

Ivan Tsmots, Vasyl Rabyk and Oleksa Skorokhoda 1/34

DESIGN OF SPECIALIZED SYSTEMS AND DEVICES

Interface-Sensitive Method of Synthesis of Microcontroller-Based System

Structures

Pavlo Denysyuk, Taras Tesluyk, Andriy Kernytskyy, Vasyl Teslyuk,

Ivan Tsmots and Oleh Berezsky 2/1

A Dynamic Programming Method of Calculating the Overlapping Allan Variance

Tetyana Marusenkova and Iryna Yurchak 2/5

Methods and Processors for Image Recognition in a Linear and Quadratic

Hamming Space

vii


Andrij Sydor, Yaroslav Nykolaychuk, Nataliia Vozna, Boris Krulikovskyi,

Alina Davletova and Oleh Liura 2/9

Ordered Access Memory Based Programmable Hardware Accelerator Parallel

Architecture

Anatoliy Melnyk and Viktor Melnyk 2/13

Algorithm for Image Transfer Using Dynamic Chaos

Olexander Belej and Tamara Lohutova 2/18

The Software for Authorship and Style Attribution

Khomytska Iryna and Teslyuk Vasyl 2/23

ARUZ Analyzer of Real Complex Systems

Andrzej Napieralski, Rafal Kielbik and Krzysztof Halagan 2/27

Using Windows Power Shell for Object-Based OLAP System Building

Mykola Fisun, Hlib Horban and Ihor Kandyba 2/31

Developing Fuzzy Traffic Managеment for Telecommunication Network Services

Ivanna Dronyuk, Yurii Klishch and Svitlana Chupakhina 2/37

Design System of Image Text Recognition Based on Neural Network

Vitaliy Yarkun, Yaroslav Paramud and Roman-Andrij Ivantsiv 2/41

Absolute and Relative Classification of Cloud Regions by Satellite Image

Clustering

Roman Melnyk, Yuriy Kalychak and Ruslan Tushnytskyy 2/45

Analysis of Positioning in Cooperative and Non-Cooperative Wireless Sensor

Networks

Oleksandr Kuzmin and Stepan Grytsishin 2/50

Modeling and Design of the Industrial Production Control Unit

Svitlana Popereshnyak and Anastasiya Vecherkovskaya 2/53

Increasing the Accessibility to Static Content Using CDN Networks as PaaS

Mykhailo Klumash, Olga Shpur, Nazar Peleh, Orest Lavriv, Roman Bak

and Olexander Skybinskyi 2/57

Problems of Designing the Information Systems for the Quality Monitoring

of Protective Consortive Ecotones

Anatoliy Obshta, Igor Kohut, Mykola Prodaniuk, Maria Ruda

and Iryna Soroka 2/61

Specialized Computer System Controlling the Technological Parameters

of the Drilling Rig

Nadiia Shyrmovska, Artur Voronych, Yaroslav Zaiachuk, Maksym Karpash

and Olha Lazoriv 2/66

The Commander’s Decision Cycle of the Situational Control System

Valery Shestakov and Yuriy Danyk 2/71

Design Method Based on Logical Assertions

Dmitry Zerbino and Iryna Yurchak 2/77

Spatial-Temporal Transformation of Sorting Algorithm with "Perfect Shuffle"

Volodymyr Gryga, Yaroslav Nykolaichuk, Artur Voronych, Ihor Pitukh

and Orest Volynskyi 2/81

Data Transmission System for a Distributed Real-Time Information-Control

System

Vitaliy Mazur and Volodymyr Karkulovskyy 2/86

Information Technology for Modeling of Atmosphere Pollution Processes

by Motor Vehicle Harmful Emissions

Mykola Dyvak, Yurii Maslyiak and Andriy Pukas 2/91

viii


MODELS AND METHODS FOR RADIOELECTRONICS DEVICE AND SYSTEM

DESIGN

Neural Network-Based Prediction of Visual Quality for Noisy Images

Andrii Rubel, Oleksii Rubel and Vladimir Lukin 3/1

Implementation Features of Composite Materials Effective Mechanical

Characteristics Finding Method Based on Microlevel Cellular Structural Models

Nazariy Jaworski, Marek Iwaniec and Mykhailo Lobur 3/6

On Intelligent Agent-Based Simulation of Network Worms Propagation

Dmytro Chumachenko and Sergiy Yakovlev 3/11

Use of Genetic Algorithm for Optimal Codes Search

Roman Yankevych, Ivan Prudyus and Volodymyr-Myron Miskiv 3/15

Modelling Features of Switching Device Errors for 2-out-of-3 and Sliding

Redundancy Systems Based on k-Terminal Dynamic Fault Tree

Serhiy Shcherbovskykh, Tetyana Stefanovych and Mykhaylo Lobur 3/19

Detection of Unoccupied Frequency Channels in Cognitive Radio Networks

Valeriy Bezruk, Stanislav Ivanenko and Aleksey Fedorov 3/23

Development of an Automated Subsystem for Modeling and Calculating a Mirror

Antenna from its Guiding and Tracking the Target

Ivan Kozemchuk, Kostyantyn Kolesnyk, Roman Panchak and

Zoryana Skybinska 3/27

The Method of Clustering Information Resource Data on the Sign of the Number

of Series of Units as a Tool to Improve the Statistical Coding Efficiency

Vladimir Barannik, Ivan Tupitsya, Oleksandr Dodukh, Valeriy Barannik

and Maksym Parkhomenko 3/32

Technology for Efficient Encoding of Structural Components Using

the Multi-Agent Approach for Telecommunication Tools and Devices

Vladimir Barannik, Oksana Stetsenko, Anton Sorokun, Alexander Musienko

and Oleksandr Yudin 3/36

Investigation of Back Scattering Properties of Thin Films Consisting of a Set

of Small-Size Particles

Mykhaylo Andriychuk 3/40

A Simple Circuit for Decoupling of Two Dual-Frequency Antennas with Small

Frequency Ratio

Valeriy Oborzhytskyy, Ivan Prudyus and Volodymyr Storozh 3/45

Novel Approach to Computer-Aided Detection of Lung Nodules of Difficult

Location With Use of Multifactorial Models and Deep Neural Networks

Pavlo Orobinskyi, Dmytro Petrenko and Vyacheslav Lyashenko 3/49

Component Fractal Coding of Color Images

Mikola Patlayenko, Olena Osharovska and Volodymyr Pyliavskyi 3/54

Methods and Special Processors of Entropy Signal Processing

Artur Voronych, Lyubov Nyckolaychuk, Nataliia Vozna and Taras Pastukh 3/59

Development of the Balanced Queue Management Scheme with Optimal

Aggregation of Flows and Bandwidth Allocation

Oleksandr Lemeshko, Tetiana Lebedenko, Olena Nevzorova, Amal Mersni

and Aymen Al-Dulaimi 3/63

Research of the Generalized Class Orthogonal Harmonic Signals Application

Efficiency in BPL Transmission Systems

Vasyl Oreshkov, Anatoliy Lashko, Leonid Lyakhovetskyy,

Alexandr Yanevich, Irina Barba and Olena Iegupova 3/67

viv


Design of the Fast ReRoute QoS Protection Scheme for Bandwidth and Probability

of Packet Loss in Software-Defined WAN

Oleksandr Lemeshko, Maryna Yevdokymenko, Oleksandra Yeremenko,

Ahmad M. Hailan, Pavel Segečand Jozef Papán 3/72

Method of Increasing the Object Detection Probability by the Multispectral

Monitoring System

Andrii Hryvachevskyi, Sergiy Fabirovskyy, Ivan Prudyus, Leonid Lazko

and Jan Matuszewski 3/77

Model and Method for Detecting Request Signals in Identification Friend

or Foe Systems

Iryna Svyd, Ivan Obod, Oleksandr Maltsev, Inna Shtykh and

Ganna Zavolodko 3/81

Model and Method for Request Signals Processing of Secondary Surveillance

Radar

Iryna Svyd, Ivan Obod, Oleksandr Maltsev, Ganna Zavolodko, Inna Shtykh

and Halyna Maistrenko 3/85

Prediction of Visual Quality for Lossy Compressed Images

Sergey Krivenko, Mikhail Zriakhov, Nataliia Kussul and Vladimir Lukin 3/89

A Fast Algorithm for Modeling Rough Surfaces in the Remote Sensing Tasks

Anatoliy Popov, Masha Bortsova and Anton Sobkolov 3/94

Numerical Analysis of the Nanowire Unipolar Transistors

Jacek Podgórski, Janusz Woźny and Zbigniew Lisik 3/98

Structure Identification of Difference Equations with Interval Estimates of Their

Parameters

Iryna Darmorost, Mykola Dyvak, Nataliya Porplytsya and Iryna Hural 3/102

Improvement of Multiprotocol Label Switching Network Performance Using

Software-Defined Controller

Andrii Pryslupskyi, Mykola Beshley, Oleksiy Panchenko

and Marian Seliuchenko 3/106

Application of Spline-Fourier Transform for Radar Signal Processing

Volodymyr Shutko, Mykola Shutko, Olena Kolganova, Lidiia Tereshchenko

and Iuliia Silantieva 3/110

Improving the Efficiency of LTE Spectral Resources Use by Introducing

a M2M/IoT Multi-Service Gateway and Ihor Kahalo

Halyna Beshley, Mykhailo Klymash, Mykola Beshley 3/114

Analysis of Influence of Initial Conditions on Setting Weight Vector of Adaptive

Antenna Array

Mykola Moskalets, Konstantin Selivanov and Batoul Sleiman 3/118

Cumulative Rain Attenuation Probability in Ukraine

Vladimir Pavlikov, Nikolay Ruzhentsev, Simeon Zhyla, Oleksandr Tsopa,

Anton Sobkolov and Olexiy Odokienko 3/122

Modeling Linear Electrical Circuits with Time-Variable Inductances

by the Frequency Symbolic Method

Yuriy Shapovalov, Dariya Bachyk, Ksenia Сhaban and Roman Romaniuk 3/126

Techniques of Automated Processing of Kolmogorov–Chapman Differential

Equation System for Reliability Analysis of Technical Systems

Ivan Symets, Maksym Seniv, Vitaliy Yakovyna and Yuriy Bobalo 3/130

Research on the Scalability of All-Optical Switches in the OLS Networks

Volodymyr Andrushchak, Mykola Kaidan, Stepan Dumych, Yulia Pyrih

and Taras Maksymyuk 3/135

vv


Efficient Calculation Methods of Subtraction Signals Convolution

Oleksandr Tymchenko, Oleksandr O. Tymchenko, Bohdana Havrysh,

Orest Khamula, Olha Sosnovska and Svitlana Vasiuta 3/139

Analysis of Reliability, Survivability and Telemetry Data of on-Board Equipment

of Small Satellites

Vadim Skobtsov, Natalia Lapitskaja, Dmitriy Kim, Natalia Novoselova,

Roman Saksonov and Eugene Nikolaenya 3/143

OPTIMAL DESIGN PROBLEMS

Energy-Efficient Backfill-Based Scheduling Approach for SLURM Resource

Manager

Nataliia Gvozdetska, Larysa Globa, Volodymyr Prokopets 4/1

Algorithmic Model of the Cyclic Changes in the Temperature of the Solid

Under the Effect of Convective Heat Exchanges with the Environment

M. Korobchynskyi, A. Mariliv, A. Bohuslavets, S. Tsybulskyi, E. Sablina,

V. Nechepurenko 4/6

Numerical Results of Variable Radii Method in the Unequal Circles Packing

Problem

Sergiy Yakovlev, Oleksii Kartashov, Kyryl Korobchynskyi,

Bohdan Skripka 4/12

Computer Simulation of the Partitioning by Mutually Orthogonal Lines

Valentina Komyak, Oleksandr Sobol, Oleksii Kartashov, Iryna Yakovleva,

Vladimir Komyak, Alexander Danilin, Olena Lyashevskaya 4/16

Modeling and Simulation of Coverage Problem in Geometric Design Systems

Sergiy Yakovlev, Oleksii Kartashov, Valentina Komyak, Sergiy Shekhovtsov,

Oleksandr Sobol, Iryna Yakovleva 4/20

Infocommunication Networks Design with Self-Similar Traffic

Dmytro Ageyev, Aram Mohsin, Tamara Radivilova, Lyudmyla Kirichenko 4/24

HetNet Spatial Topology Design Using Mini-Batch K-means Clustering

Eugen Slapak, Juraj Gazda, Gabriel Bugar, Marcel Volosin, Denis Horvath,

Taras Maksymyuk 4/28

Optimization Model for 5G Network Planning

Oleg Bondarenko, Dmytro Ageyev, Othman Mohammed 4/32

Designing of Functionally Stable Information Systems Optimal for a Minimum

of Losses

Victor Shevchenko, Alina Shevchenko, Ruslan Fedorenko, Yurii Shmorhun,

Asadi Hrebennikov 4/36

Combinatorial Optimization Problems Solving Based on Evolutionary Approach

Аndrii Oliinyk, Ievgen Fedorchenko, Аlexandеr Stepanenko, Мykyta Rud,

Dmytro Goncharenko 4/41

Suitable Damping Control Methods for Semi-Active Dynamic Vibration Absorbers

Orest Horbay, Bohdan Diveyev, Ivan Kernytskyy, Mykhaylo Buryan,

Victoria Opalko 4/46

Signed Permutation Polytope Packing in VLSI Design

Oksana Pichugina, Oleksii Kartashov 4/50

Design and Analysis of Lab-Chip Module for Rainwater Chemical Hazards

Monitoring System

Oleh Matviykiv, Tamara Klymkovych, Nataliia Bokla, Ihor Farmaha,

Krzysztof Pytel 4/56

vvi


Simulation Features of Electrically Controlled Optical Systems Based on Polymer

Structure-Liquid Crystal

Andriy Fechan, Yuriy Bashtyk, Volodymyr Kotsun, Andriy Senyk 4/60

Synthesis the Structure of the Technological Cutting Process

Khavina I.P., Lymarenko V.V., Podorozhniak А.O., Chernykh O.P.,

Mezentsev M.V. 4/64

MODELS AND METHODS FOR MICROELECTROMECHANICAL SYSTEMS

Simulation of Porous Silicon 1-D Optical Sensor Array

Ivan Ivanov, Valeriy Skryshevsky 5/1

The Mathematical Models of Mechanical and Electromechanical Systems Study

via the Qualitative and Analytical Approach

Petro Pukach, Zinovii Nytrebych, Volodymyr Ilkiv, Myroslava Vovk,

Oksana Malanchuk 5/5

Analytical Method of Investigation of Wave Processes in Mathematical Models

of Some Dynamic Systems

Zinovii Nytrebych, Petro Pukach, VolodymyrIlkiv, Oksana Malanchuk 5/10

Monte Carlo Algorithm for Modeling Parameters in Micro and Nanosystems

Using Quadratic Irrationalities and Proportional Division

Petro Kosobuskyy, Iryna Yakymets, Roksolana Kordiuk 5/15

Good Practices of Electrothermal Simulation of p-n Structures Using Sentaurus

TCAD

Janusz Woźny, Jacek Podgorski, Ewa Raj, Zbigniew Lisik 5/19

Modelling of Microelectromechanical Inertial Sensors

O.A. Sushchenko, Y.M. Bezkorovainyi, V.O. Golytsin 5/23

Statistical Analysis of Wind Turbine Operational Data

Valeriyi Kuzmin, Maksym Zaliskyi, Olena Kozhokhina, Olga Shcherbyna,

Roman Odarchenko 5/28

Order Relation on Scalar Products in Real Linear Spaces

Volodymyr Ilkiv, Zinovii Nytrebych, Petro Pukach, Ihor Kohut,

Bohdan Pakholok 5/32

Simulation and Analysis of the Magnetic Field Distribution in a Magneto-Solid

Layer

Yaroslav Pelekh, Tetiana Maherovska, Andrii Kunynets, Serhii Mentynskyi,

Roksolyana Stolyarchuk, Bohdan Pakholok 5/36

Modeling and Calculation of the Temperature-Force Regime of Functioning

of a Spherical Bimetallic Sensor in a Nonstationary Electromagnetic Field

Roman Musii, Nataliia Melnyk, Khrystyna Drohomyretska,

Olga Veselovska, Oleksandra Hasko, Oksana Puha 5/41

Modeling and Calculation of the Temperature-Force Regime of Functioning

of an Electrical Conductive Spherical Sensor Under the Action of an Amplitude-

Modulated Radio Pulse

Roman Musii, Nataliia Melnyk, Veronika Dmytruk, Oryslava Bilyk,

Beata Kushka, Hanna Shayner 5/45

Designing of Z-axis Accelerometer with Asymmetric Proof-Mass Using Surface

Micromachining Process

Cezary Maj, Michal Szermer 5/49

Considerations on Electronic System Compact Thermal Models in the Form of

RC Ladders

vvii


Marcin Janicki, Andrzej Napieralski 5/54

Influence of the Thickness of a Metal Nanofilm on the Spectrum of Surface

Plasmons

Kostrobiy Petro, Vitalii Polovyi 5/58

Geometry Details Influenced on Vibratory Microgyroscope Performance

Jacek Nazdrowicz, Andrzej Napieralski 5/62

MEMS Rotational Gyroscope Operation in Various Temperature Environment

Jacek Nazdrowicz, Andrzej Napieralski 5/66

PRACTICAL APPLICATIONS OF CAD SYSTEMS

Hull Parametric Modeling of a Small Waterplane Area Twin Hull Ships

Anzhela Boiko, Oleksandr Bondarenko, Yevhen Davydenko 6/1

Performance Prediction Method for Embedded Systems Products

Zhanna Kaminska, Serhii Serdiuk 6/5

Estimation of Noise Hazards in Environmental Monitoring Tools Design

in the Subway

Volodymyr Petrivskyi, Victor Shevchenko, Oleksiy Bychkov,

Maksym Brazhenenko 6/10

High Performance Computing System Design for ANSYS CFD and

Mechanical Codes

Andrii Golovynskyi, Volodymyr Sirenko, Taras Lazariev,

Volodymyr Savyak 6/14

Cloud Based Architecture Design of System of Systems

Maksym Brazhenenko, Pavlo Kozachok, Volodymyr Petrivskyi 6/19

Method of Artificial Neural Network Synthesis for Using in Integrated CAD

Serhii Leoshchenko, Andrii Oliinyk, Sergey Subbotin,

Serhii Shylo, Vadym Shkarupylo 6/24

A New Approach for Designing and Approbation of Laser-Based 3D Scanner

Nazariy Andrushchak, Serhiy Klyuchkovskyy, Yaroslav Neznaradko,

Vladyslav Hnatiuk 6/30

Structural Parameters Influence on a Soft Robotic Manipulator Finger Bend

Angle Simulation

Viktoriia Bortnikova, Vladyslav Yevsieiev, Vladimir Beskorovainyi, Igor Nevliudov, Iryna Botsman, Svitlana Maksymova 6/35

Synthesis of Neurocontroller for Intellectualization Tasks of Process Control Systems

Taras Teslyuk, Vasyl Teslyuk, Pavlo Denysyuk, Ivan Tsmots, Oleh Berezsky, Mykhaylo Melnyk 6/39

TECHNOLOGIES FOR MEDICINE

Computer Aided System of Time Series Analysis Methods for Forecasting

the Epidemics Outbreaks

Yulia Polyvianna, Dmytro Chumachenko, Tetyana Chumachenko 7/1

Investigation and Realisation of Prototyping Technologies for Robotic-

Prostheses Computer Aided Design

Anzhelika Parkhomenko, Olga Gladkova, Yaroslav Zalyubovskiy 7/5

Electrocardiogram Processing System Design with Parallel Computing

and Memory Transferring Using Fuzzy ART Neural Network

Serhii Shatnyi, Pavlo Tymoshchuk 7/9

mailto:[email protected]

vviii


Algorithm Reliability of Kalman Filter Coefficients Determination for Low-

Intensity Electroretinosignal

Pavlo Tymkiv, Yuriy Leshchyshyn 7/14

The Method of Indirect Restoration of Human Communicative Function

Oksana Dozorska, Evhenia Yavorska, Vasil Dozorskyi, Iryna Pankiv,

Iryna Dediv, Leonid Dediv 7/19

Concept of an Electronic Device Dedicated to Imbalance Disorders Monitoring

Mariusz Jankowski, Michal Szermer, Piotr Amrozik 7/23

3D Modeling of Aesthetic Breast Prosthesis

Nataliya Liubarenko, Julia Antonova-Rafi, Igor Khudetskyy 7/27

A Model for the Calculation of the Thrust Force and Torque During Bone Tissue

Drilling

Oleksiy Kyrkach, Valeriy Khavin, Boris Kirkach 7/33

Comparison of High-Frequency Ablation and Convectional-Infrared Coagulation

Usage in the Treatment of Arrhythmias During Opened-Heart Surgery

Igor Khudetskyy, Yurii Stasiuk, Vitalii Maksymenko,

Yuliia Antonova-Rafi 7/38

CAD Technology in Development of the Spinal Traction Therapy Smart Systems

Kostiantyn Chornyi, Khudetskyy Igor, Antonova-Rafi Yuliya 7/42

INDEX OF AUTHORS i/1

IEEE Ukraine Section - repo.knmu.edu.ua

Documents

Transcript of IEEE Ukraine Section - repo.knmu.edu.ua