<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Information Model of Ecological Systems on the Basis of Reliability and Radiocapacity with Application of GIS Technologies</article-title>
      </title-group>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>College of Engineering, Prince Sattam Bin Abdulaziz University, Department of Computer Engineering and Networks</institution>
          ,
          <addr-line>Wadi Addawasir, KSA</addr-line>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>I. Horbachevsky Ternopil National Medical University</institution>
          ,
          <addr-line>Ternopil</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>National Aviation University</institution>
          ,
          <addr-line>Kyiv</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>1878</year>
      </pub-date>
      <fpage>0000</fpage>
      <lpage>0002</lpage>
      <abstract>
        <p>In this paper the model approach based on application of analytical GIS technology for description of radioecological processes in real l andscapes was presented. The problem of verification of chamber models on the basis of field data is realized by modeling of ecological risks for ecosystem biota. The thesis presents the results of modeling the process of radionuclide migration along the trophic chain: “soil” - “fodder plants” - “cow” - “milk” “man”, - in the conditions of Volyn region (cesium-137) using the example of village Galusia.</p>
      </abstract>
      <kwd-group>
        <kwd>radionuclide migration</kwd>
        <kwd>population</kwd>
        <kwd>collective radiation exposure</kwd>
        <kwd>chamber models</kwd>
        <kwd>geographical informational systems (GIS)</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>System approach to studying ecological objects is necessary condition of current
researches in ecology. Wide range of different methods is applied for investigating
natural phenomena:
-methods of data collecting by means of different equipment and technical means;
-methods of processing obtained information, its reduction, compression and
generalization;
- methods of interpreting obtained actual material.</p>
      <p>Complexity and longtermness are peculiarities of modern ecological researches by
means of equipment: observations of living organisms and environmental factors on
chosen areas of an ecosystem are carried out for sufficiently large time interval.
Besides complex observations on stationary areas, global monitoring of ecosystems and
the whole biosphere can be fulfilled. Experiments play an important role in ecological
investigations.</p>
      <p>
        However, field monitoring cannot be considered as a single approach to ecological
processes investigation, and firstly because of limitation of time and hardware
possibilities. Modern ecological researches are characterized by more and more application
of modeling methods and firstly mathematical methods. The sense of mathematical
modeling is construction of simplified, generalized abstract model of the investigated
system, and by changing its parameters it is possible to assess and predict its
development, make decision for providing its ecological safety [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ].
      </p>
      <p>
        Development of geographical informational systems (GIS) leads to wider
application of mathematical-cartographic methods in ecological investigations, which
combine cartographic model reflecting spatial differentiation of ecosystem
components’ states and mathematical model of system’s dynamics. The GIS concept itself
includes comprehensive possibilities of collecting, integration and analyses of data
distributed in space or attached to concrete territory. Due to this GIS-technologies are
used successfully in ecological investigations, in particular, for creation of maps of
main environmental parameters. Results of modeled pollution calculations can be
imposed on natural maps of vegetation, agricultural sites and housing area. It is
possible to state with certainty that namely GIS will be one of main branches of application
of new informational technologies for solving problems of natural resource
management, assessment, prediction and planning of environmental state, providing
ecological safety [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ].
2
      </p>
    </sec>
    <sec id="sec-2">
      <title>Problem Statement</title>
      <p>After accidents on the Chernobyl nuclear power plant and Fucushima-1 mass field
researches on levels of radionuclide contamination of natural habitats – atmosphere,
soil, plants and animals – began to be conducted. They are extensive investigations
which need systematization and formalization by specially developed models and
algorithms. Acting means and schemes of environmental monitoring cannot fully
reflect dynamics of migration and redistribution of radionuclides in components of
ecosystems of different types. Field monitoring is not able “to grasp the immensity”
because of time and equipment shortage. It is necessary to include different types of
modeling into research, assessment, prognosis and management of ecosystems.</p>
      <p>
        Among methods and means of radionuclides transport modeling the method of
chamber models is widespread. Velocities of radionuclides transfer between
ecosystem’s chambers are understood in two ways: 1) as the part of general reserve of
radionuclides in chambers which transfers to conjugate chambers per unit time [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]; 2) as
assessment of part of radionuclides in volume or weight unit (m3, kg, l) of some
chamber which is able to transfer into volume or weight unit of a conjugate chamber
(for example, soil – plants etc.) [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ].
      </p>
      <p>
        In the article we represent the model approach based on application of analytical
GIS technology for description of radioecological processes in real landscapes. The
problem of verification of chamber models on the basis of field data is realized by
modeling of ecological risks for ecosystem biota [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ].
      </p>
    </sec>
    <sec id="sec-3">
      <title>Chamber Models in Radioecology</title>
      <p>The method of chamber models is used for description of transfer and migration of
radionuclides in ecosystems. According to this approach the whole chain of
radionuclides transfer is divided into chambers (boxes). In mathematical models interaction
between chambers is defined by coefficients of velocities of radionuclides transfer
between chambers.</p>
      <p>The constant growth of radioactive substances and sources of ionizing radiation
use in various industries, medicine, science increases their impact on all components
of the natural environment. Therefore, radionuclides that have fallen on the territory
of Ukraine as a result of the accident at the Chernobyl nuclear power plant, by trophic
chains can form noticeable dose loads for the population of Ukraine.</p>
      <p>First of all, these are long-lived radionuclides 137Cs and 90Sr, which constitute
the main environmental danger and have a biotic character, since they are analogous
to the macroelements K and Ca, which are necessary for the life processes of plants
and animals. In Ukraine a fairly systematic and detailed monitoring of contamination
of soil, water and food with radionuclidesis carried out. The 137Cs content is measured
on human radiation meters (SICh), and then, using the models, the expected dose is
calculated for the population of settlements. Analyzing milk monitoring data, an
assessment of the so-called passport dose is carried out.</p>
      <p>But, except for assessments and monitoring of the current state of environmental
safety for settlements of Ukraine, there is an immediate need to calculate the
longterm forecast of the radioecological state. Such forecast will make it possible to carry
out a choice and substantiation of real countermeasures for the control and
management of the environmental safety of contaminated territories of Ukraine and
population. Therefore the development of relatively simple mathematical models of the
radionuclides distribution and their dynamics on the basis of field investigations is an
important and urgent problem of modern ecology. On the one hand, this approach will
allow in the future to have a valid model of radioecological safety for each specific
settlement. On the other hand, such model, based on the real parameters of the
ecosystem will assess the possible environmental risks from other pollutants (heavy metals,
herbicides, etc.). We are talking about the formation of generalized parameters of
environmental safety and environmental risks that are characteristic of a particular
settlement.</p>
      <p>In modern ecology and radioecology, enough approaches and models for
assessing ecological capacity and radiocapacity for large areas have been developed. At
the same time, there is clearly a lack of methods and models necessary for assessing
and predicting the state of local ecosystems of specific settlements.</p>
      <p>Therefore, the concretization of existing approaches and models is relevant and
important task of modern ecology. It is necessary to have a method of operative
creating environmental safety models with binding them for specific conditions of any
settlement, for the use of which environmentalists do not require complex specialized
training. Such approach will allow including into the settlement’s environmental
passport a valid mathematical model of environmental safety that can be verified by
monitoring data. The presence of such a model will allow minimizing the volume and
details of monitoring, predict critical situations in this ecosystem. This will set limits
on the ecological capacity of the ecosystem and limit excessive anthropogenic
pressure on the territory.</p>
      <p>
        The thesis presents the results of modeling the process of radionuclide migration
along the trophic chain: “soil” - “fodder plants” - “cow” - “milk” - “man”, - in the
conditions of Volyn region (cesium-137) using the example of village Galusia (Figure
1). The parameters are established and the features of this phenomenon are
investigated. This makes it possible to have methods and approaches for monitoring, predicting
and managing radioecological safety for this local ecosystem and other similar
ecosystems [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ].
      </p>
      <p>The structured block diagram of the chamber model is shown on Figure 2. The
parameters indicated in the diagram (aij) denote the transfer rates (transition) of
radionuclides between the ecosystem chambers and have a dimension: the part of
radionuclides transferred between the chambers per one year. The methods and models for
calculating the transition between cameras comprise the content of a specially
designed and protected declarative package of the utility model.</p>
      <p>
        It was found that the main dose-forming components of the agroecosystem
Galusia, are the 4 main pastures. These pastures function, in a reliable sense, as a parallel
system. According to the theory of reliability [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ], the general reliability of this
agroecosystem as a system for transporting radionuclides from a pasture to man, can be
represented approximately as a sum of the reliability parameters of the pasture blocks.
      </p>
      <p>The chamber model of this agroecosystem can be represented as a system of
blocks. It has been established that the radionuclide transport stream from each of the
four pastures forms a parallel system. Deliveries of radionuclides from pasture to the
population forms a consistent system: "soil" - "grass" - "cow" - "milk" - "meat"
"people". The reliability of such a consistent ecosystem can be represented as a
product of the reliability parameters of the component blocks that form the radionuclide
transport stream.</p>
      <p>According to the chamber model the factor of ecological capacity and
radiocapacity of a specific element of the ecosystem and / or landscape ( F j ) is determined as:
Fj </p>
      <p> aij
aij   a ji
where  aij is the sum of the rates of pollutants transition from different
components of the ecosystem to a specific element of the ecosystem — j -th (according to
chamber models), and</p>
      <p>
         a ji is the sum of the rates of pollutants transition from the j -th chamber to
other components of the ecosystem associated with it [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ].
      </p>
      <p>This factor of ecological capacity and radiocapacity determines the reliability of
the radionuclide retention (137Cs tracer) in each component of the system.</p>
      <p>On the basis of the expeditionary research, the results of observations and
calculations, estimates of the rates of transition between the chambers of the studied
agroecosystem were obtained.</p>
      <p>For simplicity it is possible to calculate the reliability of the studied agroecosystem
with average values of velocity parameters.</p>
      <p>According to the data, the calculation of the 137Cs radionuclide transfer to the
population of the village was made. This value can be used to calculate the collective
dose, using the values of dose rates for 137Cs (2×10-8 Sv/Bq). The estimated collective
dose is about 1.6 Sv/year. At the same time, the assessment of the average value of
the individual dose of people irradiation is about 1,1 mSv/year (at a rate of 1
mSv/year). Assessment of the additive to the collective dose due to the use of forest
products is 0.34 man. Sv year, and garden products - 0.2 Sv/year. Then, the total
collective dose will be about 2.14 Sv/year, and the individual dose of irradiation for each
inhabitant of the village may be 1.4 Sv/year.</p>
      <p>
        Received data allow assessing the reliability of the components of the ecosystem
by the formula (1) and, using the consistent nature of the linkage of the individual
components in the agroecosystem with the population, receiving the assessment og
the reliability of this agroecosystem as a system for transporting radionuclides from
pastures to populations. The shown approach can be applied to evaluate the
effectiveness of different types of countermeasures [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ].
      </p>
      <p>
        The system type of the radiological research of settlements covers the main links:
soils, hay, agricultural animals, milk, forest, people. This type of simulation has been
used for different types of ecosystems. Thus, models of transport of radionuclides
137Cs on a typical slope ecosystem, mountain ecosystem, lake ecosystem and cascade
of Dnieper water reservoirs have been constructed [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ].
4
      </p>
    </sec>
    <sec id="sec-4">
      <title>Analytical GIS Technology in Ecology</title>
      <p>Analysis of pollutants behavior in sloped ecosystems, which form the basis of
virtually any terrestrial landscape, showed the possibility of describing the distribution and
redistribution of radionuclides by radiocapacity theory methods with using chamber
models. Our studies have shown that the rate of radionuclide movement in the
landscape is determined mainly by several characteristics: steep slope ( P1 ), cover type (
P2 ), landscape density ( P3 ), vertical ( P4 ) and horizontal ( P5 ) migration. Rank
estimation methods were used to estimate the probabilities of the influence of these
landscape indicators on the redistribution of radionuclides. Each of the indicators is
evaluated in the range of values from 0 to 1. Because of the independence of the
landscape indicators, the overall assessment of the probability of radionuclide migration
by the elements of the landscape is defined as a general probability and is calculated
by the formula:</p>
      <p>P  P  P2  P3  P4  P ,
1 5
(2)</p>
      <p>Particular problem is represented by real landscapes, when the estimation of the
parameters of radioactivity concerns large territories, where system of factors
influencing the redistribution of radionuclides by biotic and abiotic components of
ecosystems operate. The main factors influencing the radioactivity parameters are
determined: slope steepness, type of vegetation of the surface, runoff rate, type of soil, etc.
As established from the field studies of the processes of radionuclide motion on
sloping systems and soil erosion processes under the action of surface runoff, the drainage
intensity dramatically increases with the slope steepness. According to estimates and
literary data, with the slope steepness of 1-3o, the probability of discharge per year is
0.01-0.05 from the reserve of the pollutant on this part of the slope, and with a steep
slope of 25-30 °, the probability of discharge of radionuclides and other pollutants is
tending to 1.</p>
      <p>Using the technical capabilities of the ESRI ArcGIS software product, a
modelanalytic GIS has been developed that allows analyzing and forecasting the migration
of pollutants in ecosystems. The mathematical basis of this GIS is the mathematical
model of migration of pollutants in ecosystems. The main information components of
this model are the physico-chemical and biochemical characteristics of the pollutants,
as well as the natural and anthropogenic factors of the environment. Analysis of the
initial data allows us to reach the defining blocks of the model - indicators of the rate
of discharge and removal of pollutants in ecosystems.</p>
      <p>As a result of processing the source data and analyzing it in ArcGIS using the
Spatial Analyst and 3D Analyst modules, analytic maps are created which represent
indexed raster images that are composed of pixels of a given size. Each of these pixels
has a specific digital, index or logical value that it obtains as a result of performing
calculations on one of the possible algorithms for interpolating data from the source,
raster, or vector information GIS layers.</p>
      <p>Due to the implementation of a number of spatial and mathematical calculations
with raster information layers, we can obtain a set of necessary raster-index analytic
maps with indicators of discharge, take-off and accumulation rates of pollutants for
each of the pixels, which, having a given dimension, represent an elementary spatial
unit of the terrain. Using the "Bitmap Calculator" component from the arsenal of the
Spatial Analyst module, according to the accepted mathematical model, we define the
sequence of mathematical operations that will be implemented over the index values
of the analytic cards, and also enter the layer with the data on contamination and the
number of calculation cycles that simulate the time interval (as rule in 1 year). As a
result of these calculations, we get a new index raster layer, depicting projected
pollution levels of the territory, which are investigated within a predetermined interval of
time.</p>
      <p>As a result, we obtained estimation and forecast maps for the selected polygon
(Reserve "Lesniki" in Koncha-Zaspa near Kyiv along the river). Fig. 3 shows maps of
radio intensity indices of the landscape of the original polygon (on the right) and the
structure of its relief (on the left).</p>
      <p>Using parameters that influence the redistribution of radionuclides in the
landscape, maps (Fig. 4) of the initial uniform contamination of the 137Cs landscape (on
the left) and map of redistribution of radionuclides based on the parameters 10 years
after the accident (right) were constructed. It is evident that a significant redistribution
of pollutant is expected in the studied landscape.</p>
      <p>
        This process is intensified (Fig. 5) after 20 years of evaluation (left), and 30 years
after the accident, the prediction map (right) shows the sharp concentration of
radionuclides in the landscapes (darker red paint). In our landscape, it is primarily a
swamp [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ].
      </p>
    </sec>
    <sec id="sec-5">
      <title>Verification of Models by Field Data</title>
      <p>The model must meet two requirements:
- reflect those features of the studied object, which act as a subject of research;
- be adequate to the investigated object.</p>
      <p>According to these requirements, the process of modeling itself can be divided into
four stages: qualitative analysis, mathematical implementation, verification by field
data and studying the model.</p>
      <p>Within the presented research, chamber models of the real ecosystem have been
developed and analyzed for real ecosystem of the village Galusia of the Manevitsky
district of the Volyn region affected by the accident at the Chernobyl nuclear power
plant. The models take into account all the main streams of 137Cs radionuclides. The
block diagram of chamber models contains all the main pasturelands. If necessary, the
diagram may include radionuclide streams from forest products (mushrooms and
berries), as well as from the use of garden products.</p>
      <p>As a result of the simulation, assessments and forecast of the expected
contamination of 137Cs radionuclides of human food products (milk, meat) were received, which
is reflected in the values of collective dose loads for humans.</p>
      <p>According to the simulation results, it was found that in the settlements of the type
like Galusia, notable dosage loads were formed not immediately after the accident,
but only in 1992-1994. Now, 30 years after the accident at the ChNPP, people
accumulate total collective doses of radiation from 137Cs from 40 to 80 people / Sv. In
these territories, the large contribution to the collective dose is forest products. For
villages of the Gazus type, a marked accumulation of collective dose for the
population is characteristic for the population during 30-40 years after the accident, which is
ensured by 1% of the stock of 137Cs radionuclides in this ecosystem.</p>
      <p>Thus, agroecosystems are an important source of transport of radionuclides from
the environment to humans. The greater the radioactivity factor of the entire
agroecosystem, the more reliable it is to humans (in understanding the reliability of
radionuclide deliveries).</p>
      <p>Using the rate of migration, distribution and redistribution of radionuclides of 137Cs
in agroecosystem components, as well as the cesium transition rate to all population
groups, it is possible to calculate the reliability of this agroecosystem and to estimate
the contribution of various components of the agroecosystem in generating dose loads
per population.</p>
      <p>
        Depending on the amount of radionuclides that have fallen on the territory,
countermeasures can be used, the effectiveness of which depends on many factors (for
example, soil type, humidity, rainfall, etc.) and evaluate their utility [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ].
6
      </p>
    </sec>
    <sec id="sec-6">
      <title>Conclusions</title>
      <p>Application of models and reliability theory to the study of ecological processes in
various types of ecosystems is necessary since it allows to assess the basic
characteristics and fundamental properties of ecosystems. The proposed method for assessing
the reliability of ecosystems can be used to estimate the level of contamination and
transitions of other pollutants in different ecosystems.</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          1.
          <string-name>
            <surname>Mykhalevska</surname>
            <given-names>T.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Isaienko</surname>
            <given-names>V.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Groza</surname>
            <given-names>V.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kryvorotko</surname>
            <given-names>V</given-names>
          </string-name>
          .
          <article-title>Simulation and forecasting of environment</article-title>
          ,
          <source>Textbook</source>
          , Vol.
          <volume>1</volume>
          , NAU publishing, Kyiv,
          <year>2006</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          2.
          <string-name>
            <surname>Yu</surname>
          </string-name>
          . Kutlakhmedov,
          <article-title>Way to the theoretical radio ecology</article-title>
          , Phitosociocenter, Kyiv,
          <year>2015</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          3.
          <string-name>
            <surname>Georgievskiy</surname>
            <given-names>V</given-names>
          </string-name>
          .
          <article-title>Ecological and dose models of radiation accidents</article-title>
          ,
          <source>Naukova Dumka, Kyiv</source>
          ,
          <year>1994</year>
          , 234 p.
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          4.
          <string-name>
            <given-names>Kutlakhmedov</given-names>
            <surname>Yu</surname>
          </string-name>
          .,
          <string-name>
            <surname>Matvieieva</surname>
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Groza</surname>
            <given-names>V.</given-names>
          </string-name>
          ,
          <article-title>Reliability of biological systems</article-title>
          , Phitosociocenter, Kyiv,
          <year>2018</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          5.
          <string-name>
            <surname>Matvieieva</surname>
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Azarov</surname>
            <given-names>S.</given-names>
          </string-name>
          ,
          <string-name>
            <given-names>Kutlakhmedov</given-names>
            <surname>Yu</surname>
          </string-name>
          .,
          <string-name>
            <surname>Kharlamova</surname>
            <given-names>O</given-names>
          </string-name>
          .
          <article-title>Ecosystems security against radiation influences</article-title>
          , Monograph,
          <string-name>
            <surname>NAU</surname>
          </string-name>
          , Kyiv,
          <year>2016</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          6.
          <string-name>
            <given-names>Kutlakhmedov</given-names>
            <surname>Yu</surname>
          </string-name>
          .,
          <string-name>
            <surname>Matvieieva</surname>
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Rodina</surname>
            <given-names>V.</given-names>
          </string-name>
          ,
          <article-title>Reliability of biological systems</article-title>
          , Palamarium Academic Publishing. Saarbrucken, Deutschland,
          <year>2013</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          7. Mazin Al Hadidi,
          <string-name>
            <surname>Jamil S</surname>
          </string-name>
          .
          <string-name>
            <surname>Al-Azzeh</surname>
            ,
            <given-names>R.</given-names>
          </string-name>
          <string-name>
            <surname>Odarchenko</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          <string-name>
            <surname>Gnatyuk</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          <string-name>
            <surname>Abakumova</surname>
          </string-name>
          ,
          <article-title>Adaptive Regulation of Radiated Power Radio Transmitting Devices in Modern Cellular Network Depending on Climatic Conditions, Contemporary Engineering Sciences</article-title>
          , Vol.
          <volume>9</volume>
          , № 10, рр.
          <fpage>473</fpage>
          -
          <lpage>485</lpage>
          ,
          <year>2016</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          8.
          <string-name>
            <surname>Al-Azzeh</surname>
            <given-names>J.S.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Al Hadidi</surname>
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Odarchenko</surname>
            <given-names>R.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Gnatyuk</surname>
            <given-names>S.</given-names>
          </string-name>
          , Shevchuk
          <string-name>
            <surname>Z.</surname>
          </string-name>
          , Hu
          <string-name>
            <surname>Z.</surname>
          </string-name>
          <article-title>Analysis of self-similar traffic models in computer networks</article-title>
          ,
          <source>International Review on Modelling and Simulations</source>
          , №
          <volume>10</volume>
          (
          <issue>5</issue>
          ), pp.
          <fpage>328</fpage>
          -
          <lpage>336</lpage>
          ,
          <year>2017</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          9.
          <string-name>
            <surname>Odarchenko</surname>
            <given-names>R.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Abakumova</surname>
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Polihenko</surname>
            <given-names>O.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Gnatyuk</surname>
            <given-names>S.</given-names>
          </string-name>
          <article-title>Traffic offload improved method for 4G/5G mobile network operator</article-title>
          ,
          <source>Proceedings of 14th International Conference on Advanced Trends in Radioelectronics</source>
          , Telecommunications and Computer Engineering (TCSET-
          <year>2018</year>
          ), pp.
          <fpage>1051</fpage>
          -
          <lpage>1054</lpage>
          ,
          <year>2018</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          10.
          <string-name>
            <surname>Syerov</surname>
            <given-names>Y.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Shakhovska</surname>
            <given-names>N.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Fedushko</surname>
            <given-names>S.</given-names>
          </string-name>
          <article-title>Method of the Data Adequacy Determination of Personal Medical Profiles Advances in Artificial Systems for Medicine and Education II</article-title>
          . Volume
          <volume>902</volume>
          ,
          <year>2019</year>
          . pp.
          <fpage>333</fpage>
          -
          <lpage>343</lpage>
          . https://www.springer.com/cn/book/9783030120818
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          11.
          <string-name>
            <given-names>R.</given-names>
            <surname>Odarchenko</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            <surname>Gnatyuk</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            <surname>Gnatyuk</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.</given-names>
            <surname>Abakumova</surname>
          </string-name>
          ,
          <article-title>Security Key Indicators Assessment for Modern Cellular Networks</article-title>
          ,
          <source>Proceedings of the 2018 IEEE First International Conference on System Analysis &amp; Intelligent Computing (SAIC)</source>
          ,
          <source>Kyiv, Ukraine, October</source>
          <volume>8</volume>
          -
          <issue>12</issue>
          ,
          <year>2018</year>
          , pp.
          <fpage>1</fpage>
          -
          <lpage>7</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          12.
          <string-name>
            <given-names>Z.</given-names>
            <surname>Hassan</surname>
          </string-name>
          ,
          <string-name>
            <given-names>R.</given-names>
            <surname>Odarchenko</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            <surname>Gnatyuk</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.</given-names>
            <surname>Zaman</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            <surname>Shah</surname>
          </string-name>
          ,
          <article-title>Detection of Distributed Denial of Service Attacks Using Snort Rules in Cloud Computing &amp; Remote Control Systems</article-title>
          ,
          <source>Proceedings of the 2018 IEEE 5th International Conference on Methods and Systems of Navigation and Motion Control, October 16-18</source>
          ,
          <year>2018</year>
          . Kyiv, Ukraine, pp.
          <fpage>283</fpage>
          -
          <lpage>288</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref13">
        <mixed-citation>
          13.
          <string-name>
            <surname>M. Zaliskyi</surname>
            ,
            <given-names>R.</given-names>
          </string-name>
          <string-name>
            <surname>Odarchenko</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          <string-name>
            <surname>Gnatyuk</surname>
            ,
            <given-names>Yu. Petrova. A.</given-names>
          </string-name>
          <string-name>
            <surname>Chaplits</surname>
          </string-name>
          ,
          <article-title>Method of traffic monitoring for DDoS attacks detection in e-health systems and networks</article-title>
          ,
          <source>CEUR Workshop Proceedings</source>
          , Vol.
          <volume>2255</volume>
          , pp.
          <fpage>193</fpage>
          -
          <lpage>204</lpage>
          ,
          <year>2018</year>
          .
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>