# Special Issue No. – 8, April, 2020

“Modern Approaches in Applied Mathematics” organized by ACADEMIE PAPER, LLC, Russia.

## STRAINED VALVE-HOUSING CONTACT OF HYDRAULIC STEER

#### Authors:

Petr V. Senin,Aleksei V. Stolyarov,Sergey V. Chervyakov,

#### DOI:

https://doi.org/10.26782/jmcms.spl.8/2020.04.00001

#### Abstract:

The use of hydrostatic steerage in agricultural and construction vehicles shows that, compared to traditional hydromechanical steerage, it has better balance and no steering wheels vibrations. But in certain environments, these automobiles have to work in severe conditions and the steering breaks down rather quickly. There can be multiple reasons for this – dirt, wear, excessive turn effort. The analysis of defects of the XY 145 0/1 hydraulic steers has demonstrated that 100% of breakdowns are caused by the wear of the slide valve-housing pair, i.e. this contact is limitative. Therefore, complete wear of these parts lead to the situation when turning the vehicle requires the effort exceeding normal. To find out how to increase durability of the valve-housing pair, we conducted a research of its stress-strain state. The strains in the contact can be studied with the help of the finite-element method which allows high-precision modeling of any components and mechanisms in operation. As a result, we generated a finite-element mesh with the minimal, average and maximal pressure values, transitions and deformations in elements; pressure values were presented as a graphical file with a diagram. The model of the strain state of hydraulic steer XY-145 slide valve-housing contact can be used in selecting the materials which, applied to the worn surfaces, will increase the general durability of hydraulic steers.

#### Keywords:

Steerage,hydraulic steer,fault,wear,finite-element method,

#### Refference:

I. Burumkulov F.Kh., Ivanov V.I., Velichko S.A., Ionov P.A., Suldin S.P. (2005), Increasing of reliability of NSh-U hydraulic pumps by electric spark alloying of the working surfaces of friction couples, Elektronnaya Obrabotka Materialov, Vol. 41, No. 6, 13–18 (in Russian).

II. Burumkulov F.Kh., Velichko V.I., Ivanov V.I., Ionov P.A., Okin M.A., Stolyarov A.V. (2009), Electric spark nanocomposite coatings and their wear resistance, Machinery in Agriculture, № 1, 11-13 (in Russian).

III. Burumkulov F.Kh., Ivanov V.I., Velichko S.A., Denisov, V.A. (2014), Plasticity of electrospark. Surface Engineering and Applied Electrochemistry, Vol. 50, No. 2, 106–110.

IV. Galkin V.O. (2011), Analysis of mathematical models. Binom, Мoscow, Russia. (in Russian)

V. Mamaev V.B. (2013), Analysis of tense and deformed state in elementary unit on the example of precipitation process. Izvestia BMSTU. Retrieved from http://cyberleninka.ru/article/n/analiz-napryazhennogo-i-deformirovannogo-sostoyaniya-v-elementarnom-obeme-na-primere-protsessa-osadki (in Russian).

VI. Senin P.V., Davydkin A.M., Chervyakov S.V. (2013), Malfunction causes of dosing pumps and hydraulic steers (on the example of a hydraulic steer of the XY 145-0/1 trademark). Traktora i Selkhozmashiny, №12, 38-40 (in Russian).

VII. Stolyarov A.V. (2009), Increasing TBO of axial-piston hydraulic pump with slanting sheave block for restoration and hardening of worn surfaces of components. Dissertation. Saransk, Russia(in Russian).

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## MATHEMATICAL MODELS OF WEIGHTED NETWORKS: FORMALIZING THE DESCRIPTION OF NETWORK CONFLICTS

#### Authors:

Denis G. Plotnikov,Anna S. Pakhomova,Vladimir M. Pitolin,Oksana V. Pozdysheva,Dmitry N. Rahmanin,Sergey A. Ermakov,

#### DOI:

https://doi.org/10.26782/jmcms.spl.8/2020.04.00002

#### Abstract:

The essence of the problem is that modern communications have a pronounced network character, that causes a dramatic increase in the risk of network conflicts. It has been shown that the traditional conflict with its conceptual and analytical framework in the description of conflicts in general and of information conflicts in particular is not focused on the network and the formalization of network conflicts needs to be developed. In this regard, it is expected to build on the evaluations of weighted networks, bearing in mind that the modern network is a graph with a disjoint set of vertices (users) and edges (links) on which the network filler is circulating. Its volumes and values form a statistical (accumulated) resource (filler) on the vertices of the network and a dynamic (traffic) resource (filler) passing through the edge in a unit of time. The maximum values of these resources indicate the capacity of network elements. Even the resources dynamics of conflicting networks are considered in the context of a bilateral conflict. And the changes are proposed to be evaluated by the relative sensitivity functions that provide an inseparable assessment of the parameters of interest. Evaluations of the fundamental conflict from this approach are proposed through the deflection of the conflicting resources at the appropriate time sampling. As a result of the proposed approach, analytical expressions of the sensitivity factors that allowed for a weighted classification of network conflicts were obtained. Consideration was also given to the value and volume of fillers that make up the resources of network elements. The stages of the dynamics conflict have the same interpretation. Possible attacks by the parties in the course of their conflict interaction are also being considered. Then, the article deals with the practical value of the results obtained. In this regard, we consider the possible applications for the proposed methodology. Information networks are growing in popularity, that is why we analyze the application of the results in the context of the use of malicious software and destructive content in conflicts, where a step-by-step assessment of the dynamics of conflicting resources will make it possible to produce the necessary conflict analysis. At the interconnectivity level, a possible field of application of the article results can be a competing social network, as well as a intranet impact of antagonistic content within those networks.

#### Keywords:

Information network,network conflict,network potential,network resource,sensitivity,

#### Refference:

I. Byrd, To. War with many unknowns / K. Byrd//Computerra. – M.: 2009. – No. 20. – 5 p.
II. Grinyaev, S. Russia in global information society: threats, risks and possible ways their neutralizations / S. Grinyaev, – Electron. it is this. – Access mode: http://www.noravank.am/upload/pdf/419_ ru.pdf.
III. Newman, M. E. J. A measure of betweenness centrality based on random walks/ M. E. J. Newman //Soc. Networks. 2005. – № 27. – P. 39–54.
IV. Newman, M. E. J. Ego–centered networks and the ripple effect / M. E. J. Newman //Soc. Networks. 2003. – № 25. – P. 83–95.
V. Newman, M. E. J. Finding and evaluating community structure in networks/ M. E. J. Newman, M. Girvan // Phys. Rev. E 69. 2004. – P. 72–93.
VI. Newman, M. E. J. Mixing patterns in networks / M. E. J. Newman // Phys. Rev. E 67. – 2003.
VII. Newman, M. E. J. Power laws, Pareto distributions and Zipf’s law / M. E. J. Newman. – Electronic resource. – URL: https://vk.com/dev/openapi_api.
VIII. Newman, M. E. J. The structure of scientific collaboration networks / M. E. J. Newman // Proc. Natl. Acad. Sci. USA 98. 2001. –P. 404–409.
IX. Newman, M. E. L The structure and function of complex networks/ M. E. J. Newman // SIAM Rev. 45. 2003. –P. 167–256.
X. Novoseltsev, V. I. System conflictology / V. I. Novoseltsev, – Voronezh: Quart, 2001. – 176 p.
XI. Ostapenko, G. A. Information transactions and the attacks in the sotsiotekhnicheskikh systems: organization-legal aspects of counteraction: Education guidance / G. A. Ostapenko, E. A. Meshkov; under the editorial office Yu.N. Lavrukhina. – М: The hot line – the Telecom, 2007. – 295 p.
XII. Pastor–Satorras, R. Absence of epidemic threshold in scale–free networks with connectivity correlations / R. Pastor–Satorras, A. Vespignani// Phys. Rev. Lett. – Pub.:American Physical Society. 2002. – Vol. 90, Iss. 2. – P. 1 – 4.
XIII. Pastor–Satorras, R. Epidemic dynamics, endemic states in complex networks / R. Pastor–Satorras, A. Vespignani//Phys. Rev. E. 2001. – P.101 – 104.
XIV. Pastor–Satorras, R. Epidemic spreading in complex networks with degree correlations / R. Pastor–Satorras, A. Vespignani// Contribution to the Proceedings of the XVIII SitgesConference “Statistical Mechanics of Complex Networks”. – Berlin, 2003. – P. 165 – 170.
XV. Pastor–Satorras, R. Epidemic Spreading in Scale–Free Networks / R. Pastor–Satorras, A. Vespignani// Phys. Rev. Lett. 86. 2001. – P.45 – 56.
XVI. Pastor–Satorras, R. Topology, Hierarchy, Correlations in Internet Graphs / R. Pastor–Satorras, A. Vespignani//Lecture Notes in Phisics. 2004. – Springer – P. 425 – 440.
XVII. Prilepsky, V. V. Conflicts in information telekommunika-tsionnykh systems/ V. V. Prilepsky//Education guidance. Voronezh: Voronezh. state. техн. un-t, 2004. – 144 p.
XVIII. Rozenvasser, E. N. Chuvstvitelnost of management systems of / E.N. Rozenvasser, R. M. Yusupov, – M.: Science, 1981. – 464 p.
XIX. Ruby of. Social conflict: Escalation, the deadlock, permission / D. Rubin, D. Pruyt, H. Kim — SPb.: Prime-EVROZNAK, 2001. — 325 p.
XX. Savin, L. V. Setetsentrichnaya and network war. Introduction in the concept. / L.V. Savin. – Euroasian movement, 2011. – 130 p.
XXI. Ostapenko, G.A. Analytical estimation of the component viability of distribution automated information data system / G.A. Ostapenko, D.G. Plotnicov, O.Y Makarov, N.M. Tikhomirov, V.G. Yurasov // World Applied Sciences Journal. – 2013. – 25 (3). – P. 416-420.
XXII. Ostapenko, G.A. Analytical models of information-psychological impact of social information networks on users / G.A. Ostapenko, L.V. Parinova, V.I. Belonozhkin, I.L. Bataronov, K.V. Simonov // World Applied Sciences Journal. – 2013. – 25 (3). – P. 410-415.
XXIII. Ermakov, S.A. Optimization of expert methods used to analyze information security risk in modern wireless networks / S.A. Ermakov, A.S. Zavorykin, N.S. Kolenbet, A.G. Ostapenko, A.O Kalashnikov // Life Science Journal. – 2014. – № 11(10s). – P. 511-514.
XXIV. Radko, N.M. Assessment of the system’s EPI-resistance under conditions of information epidemic expansion‏ / N.M. Radko, A.G. Ostapenko, S.V. Mashin, O.A. Ostapenko, D.V. Gusev // Biosciences Biotechnology Research Asia. – 2014. – Vol. 11 (3). – P. 1781-1784.
XXV. Radko, N.M. Peak risk assessing the process of information epidemics expansion / N.M. Radko, A.G. Ostapenko, S.V. Mashin, O.A. Ostapenko, A.S. Avdeev // Biosciences Biotechnology Research Asia. – 2014. – Vol. 11 (Spl.End). – P. 251-255.
XXVI. Ostapenko, A.G. Flood-attacks within the hypertext information transfer protocol: damage assessment and management / A.G. Ostapenko, M.V. Bursa, G.A. Ostapenko, D.O. Butrik // Biosciences Biotechnology Research Asia. – 2014. – Vol. 11 (Spl.End). – P. 173-176.
XXVII. Islamgulova, V.V. Discreet risk-models of the process of the development of virus epidemics in non-uniform networks / V.V. Islamgulova, A.G. Ostapenko,,N.M. Radko, R.K. Babadzhanov, O.A. Ostapenko // Journal of Theoretical and Applied Information Technology. – 2016. – P. 306-315.

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## AGGLUTINATIVE ARCHITECTURE

#### Authors:

Valentin N.Tkachev,

#### DOI:

https://doi.org/10.26782/jmcms.spl.8/2020.04.00003

#### Abstract:

Architectural morphogenesis has a cyclical nature.The time of existence of each cycle is connected - not necessarily when the absolute coincidence - with epochs of the civilization development, wherein technological achievements, economy, forms of the social organization and the aesthetic worldview are joined together, realized as the cultural integrity, visually ascertained by the architectural style. Each style has phases of the birth, the golden age and the stagnation. The detector of morphological changes is the minor,at first glance, signs of the object congestion of architectural forms withprominent decorative features: symbols, plastic figures and color, which are necessary or redundant. The redundancy of equipping facade surfaces with ornamental elements and decor discredit the architectural form, which takes on the label of agglutination, when elements of decor are stuck on a facade - symptoms of the style diminishment phase. The abundance and the compositional meaninglessness of agglutinates give a signal to changing the architectural paradigm and restructuring the aesthetic worldview, shortening the time frame for the architecture renewal, ultimately aimed at establishing the priority of the pure form. The pure form, out of which the ancient architecture, the international architecture and high-tech had begun, is constantly threatenedwith the agglutination. Maybe it is high time to stop the reincarnation process?

#### Keywords:

Tectonics,the expressiveness of an architectural form,phases of the style development,agglutination,agglutinates psychology of vision,

#### Refference:

I. Banham R. A look at the modern architecture. An epoch of masters. M.: Stroyizdat, 1980, 172 p.
II. G. W. F. Hegel, Aesthetics. Lectures on Fine Art, trans. T. M. Knox, 2 vols.
Oxford: Clarendon Press, 1975, 611 p.
III. Ilyin I. A. Collected Edition. Vol. 6, book 1. M.: Russkayakniga, 1996, 560 p.
IV. Leonardo da Vinci. Selection. M.: State fiction publishing house, 1952, 258 p.
V. Melvyn J. Architecture. Guide to Styles. M.: Kladez-Books, 2007, 158 p.
VI. Nikolaev B. Physical fundamentals of architectural forms. Experience of the study of the chronical deformation of buildings. St. Petersburg: 1905, 163 p.
VII. SiegfriedGiedion, Space, Time and Architecture, vol. 4th (Cambridge, Mass: Harvard University Press, 1962), 360.
VIII. Tarasova L. G. Interrelation of management processes and self-organization in the development of large cities. Saratov, Publ. House of the Saratov University, 2009, 141 p.
IX. Tasalov V. I. Essay on aesthetic ideas of the capitalist society architecture. M.: Nauka, 1979, 336 p.
X. Tkachev V. N., Semeshkina T. V. Associations in the architecture and the design. M.: MGSU Press, 2011, 224, p.

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## TRANSFORMATION OF NETWORK MODELS CONSIDERING THEIR TOPOLOGICAL PROPERTIES AND WEIGHT CHARACTERISTICS

#### Authors:

Sergey S. Kulikov,Vladimir N. Derevianko,Dmitrii O. Karpeev,Mikhail I. Bocharov,Ekaterina A. Moskaleva,Nikolai M. Radko,

#### DOI:

https://doi.org/10.26782/jmcms.spl.8/2020.04.00004

#### Abstract:

This paper proposes a method of transformation of network models, taking into account their topological properties and weight characteristics. The method is intended for the networks with a large number of vertices. Social information networks, mustering millions of users, should be considered as the most illustrative example of such. Simulation of similar networks structures takes tremendous calculation expenditures and, therefore, the authors set themselves a task to transform the initial network by means of size reduction, yet retaining its properties. Since modern corporate and global networks are suspended (all vertices and arcs have different weights – specific traffic) and heterogeneous (the number of vertices bonds varies significantly), therefore, the authors aim to (when transforming the graph) preserve all above-mentioned topological properties and weight characteristics of the analysed network. Some equivalent transformations are formalized in the form of algorithm of the researcher’s actions. Software based on this algorithm confirmed efficiency of the proposed approach. Adduced examples illustrate the peculiarities of the proposed algorithm of transformation of networks models. Emphasized results of the research are the following: for the first time an algorithm of similarity transformation offers an opportunity to reduce an initially large network into a considerably smaller network that is convenient to use in the analysis of social networks and epidemic processes of content distribution; resulting assessments of metrics and characteristics of suspended networks, in contrast to analogues, give an opportunity to consider weight properties of the network and present an apparatus for studying properties of harmful content distribution in suspended heterogeneous social networks; in this case, discrete macro-models of the epidemic process differ from the analogues, they specifically simulate a suspended heterogeneous social network, including filler of the vertices (agents quality) and network bandwidth (the traffic that passes along the communication lines of the network).

#### Keywords:

Suspended graph,vertex,traffic,algorithm,

#### Refference:

I. Bailey, P., Craswell, N., & Hawking D. (2003). Engineering a multi-purpose test collection for Web retrieval experiments. Information processing and management, 39, 853-871.
II. Bourqui, R., Gilbert, F., Simonetto, P., Zaidi, F., Sharan, U., & Jourdan, F. (2009). Detecting structural changes and command hierarchies in dynamic social networks. Advances in Social Network Analysis and Mining, 1, 83–88.
III. Chebotarev, P., &Shamis, E. (1997). The matrixforest theorem and measuring relations in small social groups. Automation and Remote Control, 58, 1505-1514.
IV. Dekker, A. (2006). Conceptual Distance in Social Network Analysis. Network Analysis Journal, 6, 1-31.
V. Dries, A., Nijssen, S., &Raedt, L.D. (2009). A query language for analyzing networks. CIKM, 3, 485-494.
VI. Ermakov, S.A., Zavorykin, A.S., Kolenbet, N.S., Ostapenko, A.G., & Kalashnikov, A.O (2014). Optimization of expert methods used to analyze information security risk in modern wireless networks. Life Science Journal, 11(10s), 511-514.
VII. Evin, I.A., &Habibullin, T.F. (2012). Social networks. Computer studies and modeling, 4(2), 423–430.
VIII. Islamgulova, V.V., Ostapenko, A.G., Radko, N.M., Babadzhanov, R.K., &Ostapenko, O.A. (2016). Discreet risk-models of the process of the development of virus epidemics in non-uniform networks. Journal of Theoretical and Applied Information Technology, 306-315.
IX. Kuwata, Y. (2009). Decomposition algorithm for global reachability analysis on a time-varying graph as applied to planetary exploration. International Conference on Intelligent Robots and Systems.
X. Monjardet, B., &Raderinirina, V. (2001). The duality between the antiexchange closure operators and the path independent choice operators on a finite set. Mathematical Social Sciences, 41, 131-150.
XI. Newman, M.E.J. (2006). Finding community structure in networks using the eigenvectors of matrices. Physical Review Letters, 74, 1-22.
XII. Ostapenko, A.G., Bursa, M.V., Ostapenko, G.A., &Butrik, D.O. (2014). Flood-attacks within the hypertext information transfer protocol: damage assessment and management. Biosciences Biotechnology Research Asia, 11(Spl.End), 173-176.
XIII. Ostapenko, A.G., Plotnikova, D.A., &Guzev, U.N. (2016). Weighted Network Metrics. Information and Security, 19(2), 258-261.
XIV. Ostapenko, G.A., Parinova, L.V., Belonozhkin, V.I., Bataronov, I.L., & Simonov, K.V. (2013). Analytical models of information-psychological impact of social information networks on users. World Applied Sciences Journal, 25(3), 410-415.
XV. Ostapenko, G.A., Plotnicov, D.G., Makarov, O.Y, Tikhomirov, N.M., &Yurasov, V.G. (2013). Analytical estimation of the component viability of distribution automated information data system. World Applied Sciences Journal, 25(3), 416-420.
XVI. Oystein, O. (1946). Mappings of Closure Relations. Annals of Mathematics, 47, 56-72.
XVII. Park, Y., Moore, C.,& Bader, J. (2010). Dynamic networks from hierarchical Bayesian graph clustering. PLoS One, 5, 8118.
XVIII. Pfaltz, J. (2006). Logical Implication and Causal. Dependency Conceptual Structures: Inspiration and Application, 1, 145-157.
XIX. Pfaltz, J. A. (2013). Mathematical Model of Dynamic Social Networks. Social Network Analysis, 3, 863-872.
XX. Radko, N.M., Ostapenko, A.G., Mashin, S.V., Ostapenko, O.A., &Avdeev, A.S. (2014). Peak risk assessing the process of information epidemics expansion. Biosciences Biotechnology Research Asia, 11(Spl.End), 251-255.
XXI. Radko, N.M., Ostapenko, A.G., Mashin, S.V., Ostapenko, O.A., &Gusev, D.V. (2014). Assessment of the system’s EPI-resistance under conditions of information epidemic expansion. Biosciences Biotechnology Research Asia, 11(3), 1781-1784.
XXII. Richards, W., &Seary, A. (2000). Eigen Analysis of Networks. The Journal of Social Structure, 2, 1-16.
XXIII. Toivonen, R., Kumpula, J.M., Saramäki, J., Onnela, J.P., Kertész, J., &Kaski, K. (2007). The role of edge weights in social networks: modelling structure and dynamics. Noise and Stochastics in Complex Systems and Finance, 6601, 3-5.
XXIV. Wax, M., &Sheinvald, J. (1997). A least-squares approach to joint diagonalization. IEEE Signal Processing Letters, 4, 52-53.
XXV. Zhao, K., Kumar, A., Harrison, T., & Yen, J. (2011). Analyzing the Resilience of Complex Supply Network Topologies against Random and Targeted Disruptions. IEEE Systems Journal, 5(1), 28-39.

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## MATHEMATICAL MODELS OF NETWORK TERRORISM: FORMALIZING THE DESCRIPTION FOR WEIGHTED NETWORKS

#### Authors:

Denis G. Plotnikov,Grigory A. Ostapenko,Vasily I. Borisov,Larisa V. Parinova,Nikolay M. Tikhomirov,

#### DOI:

https://doi.org/10.26782/jmcms.spl.8/2020.04.00005

#### Abstract:

Terrorist attacks and their probable consequences in networks are explored with the account of the network character of the modern terrorism. By using the network resources, the structure of a network conflict of terrorist character is formalized including the metrics of its depth. Probability and entropy models of a network conflict of terrorist character are proposed, taking into account the analytical estimations and regulation of risks of conflict situations occurrence. Viewing such characteristics as the value of a filler volume unit and the network bandwidth, the authors propose analytical expressions for risk, damage, chance and durability of the critical infrastructure elements.

#### Keywords:

Information network,network terrorism,network conflict model,risk analysis,critical infrastructure,

#### Refference:

I. Antsupov, A.Ya., & Shilov, A.I. (2007). Conflictology: textbook for higher educational institutions. Saint Petersburg: Sankt Peterburg.

II. Bachilo, I.L. (2001). Informational law: fundamentals of practical information science: tutorial. Moscow: M.Yu. Tikhomirov Publishers.

III. Bachilo, I.L., & Belov, G.V. (1992). On the concept of legal support of informatization in Russia. Legislative problems of society informatization. Moscow: Mir.

IV. Bachilo, I.L., Lopatin, V.N., Fedotov, M.A., et. al. (2001). Informational law: tutorial. Saint Petersburg: Law Center.

V. Byrd, K. (2009). War with many unknowns. Computerra, 20, 5.

VI. Ermakov, S.A., Zavorykin, A.S., Kolenbet, N.S., Ostapenko, A.G., & Kalashnikov, A.O. (2014). Optimization of expert methods used to analyze information security risk in modern wireless networks. Life Science Journal, 11(10s), 511-514.

VII. Grinyaev, S. Russia in the global information society: threats, risks and possible ways of their neutralization. Retrieved from: http://www.noravank.am/upload/pdf/419_ru.pdf.

VIII. Islamgulova, V.V., Ostapenko, A.G., Radko, N.M., Babadzhanov, R.K., & Ostapenko, O.A. (2016). Discreet risk-models of the process of the development of virus epidemics in non-uniform networks. Journal of Theoretical and Applied Information Technology, 306-315.

IX. Kalashnikov, A.O., Yermilov, E.V., Choporov, ON., Razinkin, K. A., & Barannikov, N.I. (2013). Attacks at crucial objects of informational and technological infrastructure: risks assessment and regulation: monograph. Voronezh: Scientific Book.

X. Korovin, V. (2009). Main military secret of the USA. Network wars. Moscow: EKSMO.

XI. Lisichkin, V., & Shelepin, L., (1999). Third world information war of nerves. Moscow.

XII. Miroshnikov, B. N. (2002). Fighting against crimes in the sphere of information technologies. Security systems, 5(47), 10-11.

XIII. Newman, M.E.J. (2001). The structure of scientific collaboration networks. Proc. Natl. Acad. Sci. USA 98, 404–409.

XIV. Newman, M.E.J. (2003a). Ego-centered networks and the ripple effect. Soc. Networks, 25, 83–95.

XV. Newman, M.E.J. (2003b). Mixing patterns in networks. Phys. Rev. E 67.

XVI. Newman, M.E.J. (2003c). The structure and function of complex networks. SIAM Rev. 45, 167–256.

XVII. Newman, M.E.J. (2005). A measure of betweenness centrality based on random walks. Soc. Networks, 27, 39–54.

XVIII. Newman, M.E.J. Power laws, Pareto distributions and Zipf’s law. Retrieved from: https://vk.com/dev/openapi_api.

XIX. Newman, M.E.J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Phys. Rev. E 69, 72–93.

XX. Nikitov, V.A. (2000). Information support of public administration. Moscow: Slavonic dialogue.

XXI. Ostapenko, A.G., Bursa, M.V., Ostapenko, G.A., & Butrik, D.O. (2014). Flood-attacks within the hypertext information transfer protocol: damage assessment and management. Biosciences Biotechnology Research Asia, 11, 173-176.

XXII. Ostapenko, A.G., Yermilov, E.V., & Kalashnikov, A.O. (2013a). Risks of lameness, chances of usefulness and component resilience of automated systems under conditions of information threats impact on them. Information and safety, 16(2), 215-218.

XXIII. Ostapenko, A.G., Yermilov, E.V., & Kalashnikov, A.O. (2013b). Innovative trends and information risks of development of the IT sphere in the context of providing crucial objects. Information and safety, 16(3), 323-334.

XXIV. Ostapenko, G.A. (2006). Stochastic Models and the Secondary Effects Analysis of the Informational-Derivative Action in the Sociotechnical Systems. CSIT 2, 32-34.

XXV. Ostapenko, G.A., Karpeev, D.O., Plotnikov, D.G., Batishchev, R.V., Goncharov, I.V., Maslikhov, P.A., et al. (2010). Risks of the distributed systems: techniques and algorithms of assessment and management. Information and safety, 13(4), 485-530.

XXVI. Ostapenko, G.A., Linets, A.L., Guzev, Yu.N., & Chapurin, E.Yu. (2015). Characteristics of the network conflict and capacities of networks. Management of information risks and safety of infocommunication systems, 4, 72-92.

XXVII. Ostapenko, G.A., Parinova, L.V., Belonozhkin, V.I., Bataronov, I.L., & Simonov, K.V. (2013). Analytical models of information-psychological impact of social information networks on users. World Applied Sciences Journal, 25 (3), 410-415.

XXVIII. Ostapenko, G.A., Plotnikov, D.G., Makarov, O.Y., Tikhomirov, N.M., & Yurasov, V.G. (2013). Analytical estimation of the component viability of distribution automated information data system. World Applied Sciences Journal, 25 (3), 416-420.

XXIX. Ostapenko, O.A. (2005). Methodology of a risk assessment and securities of systems. Information and safety, 8(8), 28.

XXX. Panarin, I.N., & Panarin, L.G. (2003). Information war and peace. Moscow: OLMA-PRESS.

XXXI. Pastor–Satorras, R., & Vespignani, A. (2001a). Epidemic dynamics, endemic states in complex networks. Phys. Rev. E., 101 – 104.

XXXII. Pastor–Satorras, R., & Vespignani, A. (2001b). Epidemic Spreading in Scale–Free Networks. Phys. Rev. Lett. 86, 45 – 56.
XXXIII. Pastor–Satorras, R., & Vespignani, A. (2002). Absence of epidemic threshold in scale–free networks with connectivity correlations. Phys. Rev. Lett. Pub.: American Physical Society, 90(2), 1 – 4.

XXXIV. Pastor–Satorras, R., & Vespignani, A. (2003). Epidemic spreading in complex networks with degree correlations. Contribution to the Proceedings of the 28th Sitges Conference ‘Statistical Mechanics of Complex Networks’. Berlin, 165 – 170.

XXXV. Pastor–Satorras, R., & Vespignani, A. (2004). Topology, Hierarchy, Correlations in Internet Graphs. Lecture Notes in Physics. Springer, 425 – 440.

XXXVI. Radko, N.M., Ostapenko, A.G., Mashin, S.V., Ostapenko, O.A., & Avdeev, A.S. (2014). Peak risk assessing the process of information epidemics expansion. Biosciences Biotechnology Research Asia, 11, 251-255.

XXXVII. Radko, N.M., Ostapenko, A.G., Mashin, S.V., Ostapenko, O.A., & Gusev, D.V. (2014). Assessment of the system’s EPI-resistance under conditions of information epidemic expansion. Biosciences Biotechnology Research Asia, 11 (3), 1781-1784.

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## MODELS OF EPIDEMIC PROCESSES IN SOCIAL NETWORKS: INFORMATION SUPPORT

#### Authors:

Andrey V. Parinov,Nikolay N. Tolstyh,Yuri K. Yazov,Vladimir I. Belonozhkin,Olga A. Ostapenko,

#### DOI:

https://doi.org/10.26782/jmcms.spl.8/2020.04.00006

#### Abstract:

This paper considers the varieties and peculiarities of content perception in social networks. It analyzes the data about communication topology and the probability of user’s infection. The methodology of the representative sampling is suggested. The authors focused on discrete simulation of the epidemic process. In this connection, the topological models were used as a triadic predicate (vertex-arc-vertex) describing the incidence and communication strength of social network users. In this context, the matrices have been built: of the vertices degree, the weighted centrality of the network elements, and the specific balance of the content volume. These matrices characterize the topological properties of the weighted (taking into account the traffic of its arcs and vertices) of the network from which then the sampling takes place. This is due to the need to reduce the size of the network being analyzed and therefore its representative truncation is carried out, i.e. the conversion of the original data to a form suitable for later simulation of epidemics. The paper introduces a fairly detailed review of the variety of content circulating in social networks. For its intended purpose, content is divided into entertainment, useful, news, user, reputation, interactive, and commercial. Special attention is paid to destructions in content as well as the ways to draw attention to it. All of this constitutes an information base for modeling the diffusion processes of content in social networks. The above matrices serve this purpose. In addition, the paper introduces the results of the proposed methodology use in application to the development of information support required for the modeling of social networks. In this context, an example of a three-dimensional illustration of the source network and its representative sample by level of specific traffic is given. The issue of the mutation of the distribution law of verteces degrees during representative sample was discussed. In the discussion of the results obtained in the paper, the directions of further improvement of the methodology has been formulated which could be used as a basis for other researchers. First of all they are the following: structural and parametric details of social networks descriptions, comprehensive research of the content constructs and ways of its promotion in the network, taking into account the change dynamics of analyzed network parameters, and users participation in several information communities at the same time. This would greatly enrich the information support for social networks modeling.

#### Keywords:

Social network,epidemic,content,probability of infection,representative sample of data,

#### Refference:

I. Find the Most Shared Content and Key Influencers. – Электрон. дан. – Режимдоступа: http://buzzsumo.com.
II. Большая инструкция для начинающих SMM специалистов Точка доступа: http://www.terehoff.com/the-best-smm-manual.html
III. https://habrahabr.ru/post/286662/.
IV. Neil Patel. How Long Should Each Blog Post Be? A Data Driven Answer –https://www.quicksprout.com/2014/03/31/how-long- should-each- blog-post- be-a- data-driven- answer/.
V. KONECT (the Koblenz Network Collection) Social Network statistics and analysis. –http://konect.uni-koblenz.de
VI. https://ru-ru.facebook.com.
VII. https://vk.com.
VIII. http://androidconnect.ru/statistika-facebook- kolichestvo-aktivnyh- polzovatelej-naschityvaetsya- okolo-1- 7-milliarda-ezhemesyachno- 2.
IX. https://plus.google.com.
X. https://soundcloud.com.
XI. https://www.youtube.com.
XII. https://www.flickr.com/
XIII. http://ratengoods.com.
XIV. https://ru.foursquare.com.
XV. http://tourout.ru.
XVI. http://www.wikireality.ru/wiki/4pda.
XVII. http://forum.xda-developers.com.
XVIII. https://www.reddit.com.
XIX. https://www.blogger.com.
XX. https://www.tumblr.com.
XXI. http://www.livejournal.com.
XXII. http://digg.com
XXIII. https://slashdot.org.
XXIV. http://www.bibsonomy.org.
XXV. http://www.advogato.org.
XXVI. http://www.last.fm/ru.
XXVII. http://www.ligo.org.
XXVIII. Ostapenko, G.A. Analytical estimation of the component viability of distribution automated information datasystem / G.A. Ostapenko, D.G. Plotnicov, O.Y Makarov, N.M. Tikhomirov, V.G. Yurasov // World AppliedSciences Journal. – 2013. – 25 (3). – P. 416-420.
XXIX. Ostapenko, G.A. Analytical models of information-psychological impact of social information networks on users /G.A. Ostapenko, L.V. Parinova, V.I. Belonozhkin, I.L. Bataronov, K.V. Simonov // World Applied SciencesJournal. – 2013. – 25 (3). – P. 410-415.
XXX. Ermakov, S.A. Optimization of expert methods used to analyze information security risk in modern wirelessnetworks / S.A. Ermakov, A.S. Zavorykin, N.S. Kolenbet, A.G. Ostapenko, A.O Kalashnikov // Life ScienceJournal. – 2014. – № 11(10s). – P. 511-514.
XXXI. Radko, N.M. Assessment of the system's EPI-resistance under conditions of information epidemic expansion‏ /N.M. Radko, A.G. Ostapenko, S.V. Mashin, O.A. Ostapenko, D.V. Gusev // Biosciences Biotechnology ResearchAsia. – 2014. – Vol. 11 (3). – P. 1781-1784.
XXXII. Radko, N.M. Peak risk assessing the process of information epidemics expansion / N.M. Radko, A.G. OstapenkoS.V. Mashin, O.A. Ostapenko, A.S. Avdeev // Biosciences Biotechnology Research Asia. – 2014. – Vol. 11(Spl.End). – P. 251-255.
XXXIII. Ostapenko, A.G. Flood-attacks within the hypertext information transfer protocol: damage assessment and
XXXIV. management / A.G. Ostapenko, M.V. Bursa, G.A. Ostapenko, D.O. Butrik // Biosciences Biotechnology ResearchAsia. – 2014. – Vol. 11 (Spl.End). – P. 173-176.
XXXV. Islamgulova, V.V. Discreet risk-models of the process of the development of virus epidemics in non-uniformnetworks / V.V. Islamgulova, A.G. Ostapenko,,N.M. Radko, R.K. Babadzhanov, O.A. Ostapenko // Journal ofTheoretical and Applied Information Technology. – 2016. – P. 306-315.

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## MODELS OF EPIDEMIC PROCESSES IN SOCIAL NETWORKS: METHODOLOGICAL SUPPORT

#### Authors:

Andrey V. Parinov,Alexander G. Ostapenko,Oleg N. Choporov,Konstantin A. Razinkin,Andrey Yu. Savinkov,

#### DOI:

https://doi.org/10.26782/jmcms.spl.8/2020.04.00007

#### Abstract:

In this paper, the micromodels of processes infection with the social networks users content as well as users in the process of two contents conflicting have been substantiated. The methodological support is suggested for epidemic risk analysis of social networks. The methodological approach is based on the probabilistic representation of the user's infection process, where its different states takes place during the content perception. For the assessment of the values of the transition probabilities between these states, the results of statistical studies obtained for networks were used : communication, media-content exchange, reviews and insights, group discussions, authors' accounts, social bookmarkings, according to interests. Moreover, the topics of content were taken into account: music, food, scenery, people, goods, restaurant, tickets, stocks, health, nuclear weapons, war, business, society, cooperation, etc. In addition, there was a recalculation in conditional probabilities when considering the problem of collision of competing contents, including the specifics of social network analysis from the point of view of risk assessment of the spreading the destructive content and the user's chances to perceive positive information. This approach actually considers the situations being relevant to network confrontation when there is a collision of competing contents in the network, and their diffusion takes place under influence of the conditional probabilities of the   network vertex transition into one or other  state of perception of these contents. In this regard, the models taking into account the loss and retention of immunity in relation to the impacted contents were considered . At the same time, the model of contents confrontation offered in the paper is arised from the capabilities of multiple states of network vertex. For this purpose, the appropriate analytical expressions for conditional probabilities of transition from the state to the state of network user have been obtained. To discuss the possible practical application of the proposed methodology,  this paper considers the analytical assessment of risks and chances of content diffusion in the network  This approach is based on the weighting of the network elements, where their  specific traffics are logically used, easily computed from these publicly available social networks. The weighted sets of infected and other vertices characterize in this case the results of the epidemic process at its different stages. The corresponding analytic expressions are also suggested for the case of several contents collision in a network.

#### Keywords:

Social network,epidemic,micromodels of the epidemic process,microfractal,

#### Refference:

I. Agarwal A. Sentiment analysis of Twitter data / A.Agarwal, B. Xie, I. Vovsha, O. Rambow, R. Passonneau// LSM ’11 Proceedings of the Workshop on Languages in Social Media, Association for Computational Linguistics.–2011.– P. 623.

II. Amna D. Social Relevance for review probabilities / D. Amna,H. Hatem // International Conference on Control, Engineering & Information Technology (CEIT’13) Proceedings Engineering & Technology. –2013. – Vol.1.
III. Bild D. Aggregate Characterization of User Behavior in Twitter and Analysis of the Retweet Graph / D.Bild, R. Dick, Y.Liu, Z.Mao //Texas CSSI.–2014.– Vol. 2.
IV. Cha M. Flash Floods and Ripples: The Spread of Media Content through the Blogosphere / M.Cha, J. A. N.Perez, H.Haddadi // 3rd Int’l AAAI Conference on Weblogs and Social Media (ICWSM) Data Challenge Workshop. – 2009.– Vol. 12.
V. Ermakov, S.A. Optimization of expert methods used to analyze information security risk in modern wireless networks / S.A. Ermakov, A.S. Zavorykin, N.S. Kolenbet, A.G. Ostapenko, A.O Kalashnikov // Life Science Journal. – 2014. – № 11(10s). – P. 511-514.
VI. Fragkiskos D. Mining Social and Information Networks / D.Fragkiskos //UCSD Artificial Intelligence Seminar. – 2016.– P. 123-145.
VII. Gao B. Topic-Level Social NetworkSearch / B.Gao, J. Tang , Y.Wan, S.Wu // 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining in New York– 2014 – P. 769–772.
VIII. Guilherme F. Role of centrality for the identification of influential spreaders in complex networks / F.Guilherme, L.Andre, M.Pablo, A.Francisco // Universidade de São Paulo, Biblioteca Digital da ProduçãoIntelectual – BDPI. –2014. – P. 2–8.
IX. Islamgulova, V.V. Discreet risk-models of the process of the development of virus epidemics in non-uniform networks / V.V. Islamgulova, A.G. Ostapenko,,N.M. Radko, R.K. Babadzhanov, O.A. Ostapenko // Journal of Theoretical and Applied Information Technology. – 2016. – P. 306-315.
X. Kristian K. Maximum Entropy Models of Shortest Pathand Outbreak Distributions in Networks / K.Kristian, H.Fabian // Cambridge University Press. –2015. – Vol. 68.
XI. LiJ.Social network user influence sense-making and dynamics prediction / J.Li,Q.Li, T.Li,W.Peng, T.Sun, J.Xu //Expert Systems with Applications.–2014. – P. 5115–5124.
XII. Mislove A. Measurement and Analysis of Online Social Networks / A.Mislove, M.Marcon, K. P.Gummadi, P.Druschel, B.Bhattacharjee, Proceedings of the 7th ACM SIGCOMM conference on Internet measurement.– 2012.– P. 29–42.
XIII. Myers S.A. Information diffusion and external influence in networks /S.A. Myers, C. Zhu, J. Leskovec//Proceedings of the 18th ACM SIGKDD international conference on knowledge discovery and data mining ACM. – 2015. – P. 33–41.

XIV. Ostapenko, A.G. Flood-attacks within the hypertext information transfer protocol: damage assessment and management / A.G. Ostapenko, M.V. Bursa, G.A. Ostapenko, D.O. Butrik // Biosciences Biotechnology Research Asia. – 2014. – Vol. 11 (Spl.End). – P. 173-176.

XV. Ostapenko, G.A. Analytical estimation of the component viability of distribution automated information data system / G.A. Ostapenko, D.G. Plotnicov, O.Y Makarov, N.M. Tikhomirov, V.G. Yurasov // World Applied Sciences Journal. – 2013. – 25 (3). – P. 416-420.

XVI. Ostapenko, G.A. Analytical models of information-psychological impact of social information networks on users / G.A. Ostapenko, L.V. Parinova, V.I. Belonozhkin, I.L. Bataronov, K.V. Simonov//World Applied Sciences Journal. – 2013. – 25 (3). – P. 410-415.

XVII. Radko, N.M. Assessment of the system’s EPI-resistance under conditions of information epidemic expansion‏ / N.M. Radko, A.G. Ostapenko, S.V. Mashin, O.A. Ostapenko, D.V. Gusev // Biosciences Biotechnology Research Asia. – 2014. – Vol. 11 (3). – P. 1781-1784.

XVIII. Radko, N.M. Peak risk assessing the process of information epidemics expansion / N.M. Radko, A.G. Ostapenko, S.V. Mashin, O.A. Ostapenko, A.S. Avdeev // Biosciences Biotechnology Research Asia. – 2014. – Vol. 11 (Spl.End). – P. 251-255.

XIX. Romero D. Differences in the mechanics of information diffusion across topics: idioms,political hashtags, and complex contagion on twitter / D.Romero, B.Meeder, J.Kleinberg // Proceedings of the 20th international conference on world wide web ACM. – 2015. – P. 695–704.

XX. Skaza J. Mathematical Modeling of Trending Topics on Twitter / J.Skaza // Senior Capstone Project for JonathanS. Skaza. –2014. – P. 3–5.

XXI. Sun E. Gesundheit! Modeling contagion through Facebook news feed / E.Sun, I.Rosenn, C.Marlow, T. Lento//ICWSM. – 2014. – P. 56-60.

XXII. Tang M. A dynamic microblog network and information dissemination in “@” mode / M.Tang, X.Mao, S.Yang, H.Zhou // Math ProblEng. – 2014. – P. 1–15.

XXIII. Tixier A. J. A Graph Degeneracy-based Approach to Keyword Extraction / A. J. Tixier, F. D.Malliaros, M.Vazirgiannis//Conference on Empirical Methods in Natural Language Processing (EMNLP). – 2016. – Vol. 22.

XXIV. Woo J. An event-driven SIR model for topic diffusion in web forums / J.Woo, H.Chen // IEEE international conference on intelligence and security informatics (ISI). – 2012. – P. 108–113.

XXV. Woo J. Epidemic model for information diffusion in web forums: experiments in marketing exchange and political dialog / J. Woo, H. Chen // Springer Plus – a Springer open journal. –2016 – P. 7–15.

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## USE OF CLUSTER ANALYSIS FOR THE CLASSIFICATION OF ABRASIVE WHEELS IN TERMS OF GROUND FACE QUALITY OF 1933Т2 ALUMINIUM ALLOY PARTS

#### Authors:

Yakov I. Soler,Chi Kien Nguyen,Van Canh Nguyen,

#### DOI:

https://doi.org/10.26782/jmcms.spl.8/2020.04.00008

#### Abstract:

Abrasive wheels are normally classified by the various signs that have to be assured at the manufacture stage. Until now, there has been a lack of the information on the assessment of the impact of abrasive wheels on output parameters of the part surface quality. This study uses the cluster analysis method to group subjects or phenomena under consideration subject to the measures of position (means, medians) and dispersion. Abrasive wheels of 14 types are classified into three groups that have similar cutting power in terms of the quality of 1933Т2 high-strength aluminium alloy ground parts. The first cluster comprises the following wheels:37C46I12VP, 37C(46,60,80)K12VP, 39C(46,80)(I,K)12VP, 08C(46,70)12V01(P01,P02), 63C40L7V; second – 5SG46K12VXP, TGX80I12VCF; third – 39C(46,60)K8VK.It has been established that, other than Russian abrasive tool 63C40L7V, the first cluster comprises high-porous wheels (HPW) by Norton and Molemad of 12th structure that yield the most precise forms and micro-hardness of parts. Cluster 3 comprises two Norton wheels with normal pores (grade 8) that yield the cleanest surface:one-two categorial values (GOST 2789–79) lower than HPW. Cluster 2 wheels were tested and showed the lowest performance.

#### Keywords:

Flat grinding,abrasive wheels,nonparametric statistics,median,measure of dispersion,cluster analysis,

#### Refference:

I. Abrasive Articles with Novel Structures and Methods of Grinding: US Patent 7275980 / A. Bonner [et al.] /Saint–Gobain Abrasives Technology Company: filed March 21, 2003; publ. October 2, 2007.

II. Anderberg M.R. Cluster Analysis for Application. New York, Academic Press, 1973. P. 359.

III. Dulichenko I.V. Management of process characteristics of the grinding by high-porous abrasive tools [Upravleniyetekhnologicheskimikharakteristi-kamiprotsessashlifovaniyavysokoporistymabrazivnyminstrumentom]. Extended abstract of Ph.D. thesis in Engineering: 05.03.01 / Dulichenko Igor Viktorovich. Volgograd, 2006. P. 15.

IV. Duran B., Odell P. Cluster analysis. Moscow: Statistics, 1977. P. 128.

V. GOST 24642-81. Tolerances of form and position. Basic terms and definitions. Effective as of July 1, 2006. Moscow: Publishing house of standards, 1981. P. 68.

VI. GOST 25142-82. Surface roughness. Terms and definitions. Effective as of January 1, 1983. Moscow: Publishing house of standards, 1987. P. 22.

VII. GOST 25142-82. Surface roughness. Terms and definitions. Effective as of February 18, 1982. Moscow: Publishing house of standards, 1982. P. 22.

VIII. GOST 2789-73. Surface roughness. Parameters, characteristics and designations. Effective as of January 1, 1975. Moscow: Publishing house of standards, 1973. P. 10.

IX. GOST 3647-80. Abrasives. Grain sizing. Graininess and fractions. Test methods. Effective as of January 1, 1982. Moscow: Publishing house of standards, 2004. P. 19.

X. GOST 9450-76. Measurements of microhardness by diamond instruments indentation. Effective as of January 1, 1977. Moscow: Publishing house of standards, 1993. P. 36.
XI. GOST R 52381-2005. Abrasive materials. Grain and grain size distribution of grinding powders. Test of grain size distribution. Effective as of July 1, 2006. Moscow: Standartinform, 2005. P. 15.

XII. GOST R 52587-2006. Abrasive tools. Designations and hardness test methods. Effective as of January 1, 2008. Moscow: Standartinform, 2007. P. 12.

XIII. GOST R ISO 5725-2-2002. Accuracy (trueness and precision) of measurement methods and results. Part 2. Basic method for the determination of repeatability and reproducibility of a standard measurement method. Effective as of January 11, 2002. Moscow: Publishing house of standards, 2002. P. 58.

XIV. Hollander M., Wolfe D.A. Nonparametric statistical methods. New Jersey, Wiley–Interscience, 1999. P. 787.
XV. ISO 1365–3: 2000. Geometrical product specifications (GPS). Surface texture: Profile method. Surfaces having stratified functional properties. Part 3: Height characterization using the material probability curve. Geneva, International Standard, 2000. P. 20.

XVI. Jackson M.J., Davim J.P. Machining with Abrasives. Springer, 2011. P. 423.

XVII. Jambu M. Multivariate cluster analysis and regularities. Moscow: Finance and statistics, 1988. P. 342.

XVIII. Kremen Z.I., Yuryev V.G. Grinding with super abrasives of high-ductile alloys [Shlifovaniyesuperabrazivamivysokoplastichnykhsplavov]. St.-Petersburg: Polytechnic University publishing house, 2013. P. 167.

XIX. Mandel I.D. Cluster analysis. Moscow: Finance and statistics, 1988. P. 176.

XX. Pollard J. Reference book on computation statistical methods // Translation from English. Finance and statistics, 1982. P. 344.

XXI. SolerYa.I., Mai Dinh Si. Assessment of the impact of Norton high-porous abrasive discs made of black silicon carbide on the accuracy of the form of ground parts made of BT20 [Otsenkavliyaniyavysokoporistykhabrazivnykhkrugov Norton izchernogokarbidakremniyanatochnostformyshlifuyemykhdetaleyiz VT20] // News of the Samara Scientific Center of the Russian Academy of Sciences, 2015. Vol. 17. No. 6(2). P. 472–478.

XXII. SolerYa.I., Mai Dinh Si. Increasing the effectiveness of the usage of silicon carbide abrasive wheels for the flat grinding of BT20 titanium alloy [Povy-sheniyeeffektivnostiispolzovaniyakarbidkremniyevykhabraziv-nykhkrugovpriploskomshlifovaniititanovogosplava VT20] // Bulletin of the Irkutsk State Technical University, 2016. No. 8(115). P. 43–56.

XXIII. SolerYa.I., Nguyen Van Canh, Kazimirov D.Yu. Classification of flat instrumental plates by topography of ground surface using cluster analysis // ARPN Journal of Engineering and Applied Sciences, 2016. Vol. 11. Issue 21. P. 12715 – 12723.

XXIV. SolerYа.I., Nguyen Chi Kien. Forecasting grain contribution of highly wheels Norton in the formation of microrelief flat parts of high-strength aluminium alloy 1933T2 / Ya.I. Soler, C. K. Nguyen // International Scientific Review. London, United Kingdom. 2015. No. 6 (7). P. 7–17.

XXV. SolerYа.I., Nguyen Chi Kien. Statistical assessment of grindability of flat parts made of aluminium alloys [Statisticheskiyeotsenkishlifuyemostip-loskikhdetaleyizalyuminiyevykhsplavov] // Fundamental and experimental challenges related to methods and technology, 2017. No. 5 (325). P. 53-64.

XXVI. Suslov A.G. Technological support of the parameters of the condition of the surface layer of the parts [Tekhnologicheskoyeobespecheniyeparame-trovsostoyaniyapoverkhnostnogosloyadetaley] / Suslov A.G. Moscow: Mashinostroyeniye publishing house, 1987. P. 208.

XXVII. Tawakoli T. High–Efficiency Deep Grinding: Technology, Process Planning and Economic Application / ed. C.G. Barrett. Düsseldorf: VDI–Verlag; London: Mechanical Engineering Publications, 1993. P. 141.

XXVIII. Webster J., Tricard M. Innovations in Abrasive Products for Precision Grinding // CIRP Annals – Manufacturing Technology. Vol. 53. Issue 2. P. 597–617.

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## ULTRA-WIDEBAND DIVIDERS-COMBINERS OF PICO- AND NANOSECOND SIGNALS

#### Authors:

Vyacheslav N. Fedorov,Nikolay D. Malutin,Nikolay B. Drobotun,

#### DOI:

https://doi.org/10.26782/jmcms.spl.8/2020.04.00009

#### Abstract:

Specific features of the operation of ultra-wideband power dividers based on coupled lines under the influence of picosecond impulses are considered. The divider consists of seven links: a single-stage splitter on a three-wire strip line and six cascades of quarter-wave transformers on two-wire coupled lines. The possibility of using dividers as combiners of pulse signals fed to the outputs of the dividers is shown. It is shown that the decoupling of the output ports and the transmission factor between the input port and the output ports, measured in the pulsed mode and under the influence of the chirp signal, are significantly different. Conditions for increasing the decoupling of the divider outputs in the pulsed mode are given.The divider is made on a ceramic substrate with an area of 5.5×1.2 mm and provides decoupling in the frequency band from 10 GHz to 67 GHz not worse than 18 dB, and maximum return losses not worse than 12 dB at insertion loss from –3,5 to –4.4 dB in frequency range.

#### Keywords:

A super-broadband divider,the combiner of impulses,picosecond and nanosecond impulses,divider model as a six-pole,ABCD-matrix of divider/combiner,boundary conditions for the incident and the reflected waves in microwave devices,

#### Refference:

I. A.M. Nicolson, C.L. Bennett, D. Lamensdorf, and L. Susman, Application of Time-Domain Metrology to the Automation of Broadband Microwave Measurement, IEEE Trans. Microwave Theory Tech., 1972, Jan.,v. 20, No1, PP.3-9.
II. Analysis and Design of Integrated Circuit– Antenna Modules Edited by K.C. Gupta, Peter S. Hall, 2000, John Wiley & Sons, Inc., 424 p.
III. EnricMiralles, Bernhard Schönlinner, Volker Ziegler, and Frank Ellinger, Fast design method and validation of very wideband tapered Wilkinson divider, 2015 European Microwave Conference (EuMC), 2015, P. 119 – 122. DOI: 10.1109/EuMC.2015.7345714.
IV. Harmuth H.R., Boules R.N., Hussain M.G.M. Electromagnetic Signals: Reflection, Focusing, Distortion and Their Practical Applications; – New York: Kluwer Academic / Plenum Press, 1999. 214 p.
V. In Bok Kim; Ki Hyuk Kwon; Seung Bok Kwon; WahabMohyuddin; Hyun Chul Choi; Kang Wook Kim, Ultra-wideband multi-section power divider on suspended stripline, 2017 IEEE MTT-S International Microwave Symposium (IMS), 2017, Pp. 427 – 430. DOI: 10.1109/MWSYM.2017.8058587.
VI. Lingxiao Jiao, Yongle Wu, Yuanan Liu, QuanXue, and ZabihGhassemlooy, Wideband Filtering Power Divider With Embedded Transversal Signal-Interference Sections, IEEE Microwave and Wireless Components Letters, vol. 27, No. 12, December 2017, pp. 1068-1070. DOI:10.1109/LMWC.2017.2758761.
VII. N. Kheirodin, L. Nevou, H. Machhadani, P. Crozat, L. Vivien, M. Tchernycheva, A. Lupu, F.H. Julien, G. Pozzovivo, S. Golka, G. Strasser, F. Guillot, and E. Monroy. Electro optical Modulator at Telecommunication Wavelengths Based on GaN–AlN Coupled Quantum Wells, IEEE Photonics Technology Letters, 2008, Vol. 20, Issue 9. Pp. 724 – 726.
VIII. Nam S., El-Ghazaly S., Ling H., Itoh T. Time-Domain Method of Lines // IEEE MTT-S Int. Microwave Symp. Dig., 1988, May. -PP.627-630.
IX. Nikolai Drobotun, Dmitry Yanchuk, EvgenyKhoroshilov. Compact Planar Ultra-Wideband Power Dividers with Frequency Range up to 67 GHz for Multichannel Receivers, Proceedings of the 46th European Microwave Conference, 3-7 October 2016. London, UK, 2016. Pp. 198-201.
X. OkanÜnlü, Ultra wideband tapered power combiner/divider M.S. in Electrical and Electronics Engineering, Supervisor: Prof. Dr. Abdullah Atalar, October, 2014, 75 pp.
XI. Tzu Han Wang, and JauHrong Chen, Power recycling using Wilkinson power combiner with pulsewidth modulation, 2017 IEEE International Symposium on Radio-Frequency Integration Technology (RFIT), Year: 2017, Pages: 223 – 225. DOI: 10.1109/RFIT.2017.8048257.

XII. Ultra-wideband (UWB) Wilkinson power divider with ultra-narrow dual-notched bands using embedded CPW resonators, Jie Zhou; Huizhen Jenny Qian; Darong Huang; XunLuo, 2017 IEEE MTT-S International Microwave Symposium (IMS), 2017, Pp. 416 – 419. DOI: 10.1109/MWSYM.2017.8058583.
XIII. V.N. Fedorov, and N.D. Malyutin, Nonlinear Properties of a Strip Transmission Line Based on Carbon Fiber, 2016 International Symposium on Fundamentals of Electrical Engineering. University Politechnica of Bucharest, Romania, June 30 – Julay 2, 2016. DOI:10.1109/ISFEE.2016.7803222.
XIV. V.N. Fedorov, N.B. Drobotun, P.A. Mikheev and N.D. Malyutin, A demultiplexing unit for separating incident and reflected nano- and picosecond pulse signals, Instruments and Experimental Techniques, Vol. 60, Issue 1, 1 January 2017, Pp. 58-60. DOI: 10.1134/S0020441217010018.
XV. Vincent F. Fusco, Microwave Circuits Analysis and Computer-Aided Design. Prentice-Hall International (UK) Ltd., 1987.
XVI. Xuedao Wang, Jianpeng Wang, Gang Zhang, Jia-Sheng Hong; and Wen Wu, Dual-Wideband Filtering Power Divider With Good Isolation and High Selectivity, IEEE Microwave and Wireless Components Letters, 2017, Vol. 27, Issue: 12, pp. 1071 – 1073. DOI: 10.1109/LMWC.2017.2758318.
XVII. М. Ghavami, L.B Michael., R. Kohno. Ultra Wideband Signals and Systems in Communication Engineering. – London: John Wiley & Sons, 2004.

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## SELECTION OF OPTIMAL METHOD OF CORRELATED COLOUR TEMPERATURE CALCULATION

#### Authors:

Olga E. Zheleznikova,Sergey V.Prytkov,Andrey M. Kokinov,

#### DOI:

https://doi.org/10.26782/jmcms.spl.8/2020.04.00010

#### Abstract:

Correlated color temperature (CCT) is a value that characterizes thechromaticity of radiation and it is also used for calculation of color rendering according to the metrics CRI and CQS and also in the theoretical researches. And if in the first case the specific accuracy is not required during its estimation because there are chromatic thresholds within the limits of which CCT is accepted to be the same, in the second and the third cases the accuracy of the methods cannot be neglected. Also, due to the fact that there are several methods of the CCT calculation, all of them possess different degree of complexity and accuracy and the researchers face the problem what method and in what case they shall prefer.The above mentioned determines the urgency of the studied problem. The objective of the article is to determine the distribution of the CCT absolute error in the field of its determination for the most well-known methods: Robertson’s method, Yoshi Ohno’s method, Javier Hernandez-Andres’ method, McCamy’s method. The leading approach to the research of this problem is to use the coordinates of chromaticity located on the lines of the constant correlated color temperature with the further evaluation of the absolute error as the initial data for the CCT calculation. As a result of the research it was revealed that the numerical methods of Robertson and Yoshi Ohno are significantly more precise than the analytical methods of Hernandez-Andres and McCamy in the whole CCT definition domain. On the base of the obtained distributions of the absolute error the recommendation can be given to use the different methods of calculation for different cases. The work compares the “classical” variant of Robertson’s method using the 31 isotherm and the variants with a bigger number of isotherms. It is shown that when the step between the isotherms is reducing the error is decreasing too. The developed method of estimation of the CCT calculation is universal and can be applied to other methods apart the methods considered in the article.

#### Keywords:

Correlated color temperature,Planckianlocus,blackbodylocus,line of constant correlated temperature,chromaticity coordinates,absolute error,

#### Refference:

I. 12Schanda, J., 2007. Colorimetry.Understanding the CIE system, pp: 499.

II. C. S. McCamy, “Correlated color temperature as an explicit function of chromaticity coordinates,” Color Res. Appl. 17, 142–144 (1992).

III. CIE 15: Technical Report: Colorimetry, 3rd edition. – 2004.

IV. Hernandez-Andres, J, 1999. Calculating correlated color temperatures across the entire gamut of day light and sky light chromaticities. Journal Of The Optical Society Of America, 38 (27): 5703 –5709.

V. Kelly, K. L. Lines of Constant Correlated Color Temperature Basedon Mac Adam’s (u,v) Uniform Chromaticity Transformation of the CIE Diagram/ K. L. Kelly // JournalOfTheOpticalSocietyOfAmerica. – 1963. – V 53, N 8. – pp. 999- 1002.

VI. Krystek M. Analgorithm to calculate correlated colour temperature/M. Krystek// Color Res. Appl. 10, 38–40. – 1985.

VII. Matplotlib [Electronicsource]. – Electronic data and programs– Accessmode:http://matplotlib.org/, free. – Accessed date: 21.12.17

VIII. Numpy [Electronicsource]. – Electronic data and programs– Accessmode: http://www.numpy.org/, free. – Accessed date: 21.12.17

IX. Ohno, Y., 2013. Practical Use and Calculation of CCT and Duv. The Journal of the Illuminating Engineering Society of North America, pp: 47-55.

X. Ohta, N., Robertson, A. R., 2005. Colorimetry. Fundamentals and Applications, pp: 354.

XI. Prytkov, S. V., 2015. Calculations of lines of constant correlated color temperature. Problems and perspectives of development of national lighting engineering, electrical engineering and power engineering: materials of the XII All-Russian Scientific and Technical Conference with international participation, Saransk, p.:191-196.[Prytkov, S. V., 2015. O raschetepostoyannoykorrelirovannoytsvetovoytemperatury. Problemiperspektivyrazvitiyaotechestvennoysvetotekhniki, elektrotekhniki i energetiki: mat. XII Vseros. Nauch.-tekh.konf.Smezhdunar. Uchastiem, Saransk, s.:191-196.]

XII. Prytkov, S. V., 2015. New calculation table to determine correlated color temperature according to Robertson’s method. Problems and perspectives of development of national lighting engineering, electrical engineering and power engineering: materials of the XII All-Russian Scientific and Technical Conference with international participation, Saransk,p.: 196 – 202. [Prytkov, S. V., 2015. Novaya raschetnayatablitsadlyaopredeleniyakorrelirovannoytsvetovoytemperaturypometoduRobertsona. Problemiperspektivyrazvitiyaotechestvennoysvetotekhniki, elektrotekhniki i energetiki: mat. XII Vseros. Nauch.-tekh.konf.smezhdunar. uchastiem, Saransk, s.: 196 – 202.]

XIII. Python [Electronic source]. – Electronic data and programs – Access mode: https://www.python.org/, free. – Accessed date: 12.04.15 17 Tarrant A. W. S. Thespectralpowerdistributionofdaylight/ A. W. S. Tarrant// Trans. Illum. Eng. Soc. 33, 75–82. –1968

XIV. Robertson, A. R. 1968. Computation of correlated color temperature and distribution temperature. Journal Of The Optical Society Of America, 58: 1528 –1535.
XV. Schanda J. “Correlatedcolortemperaturecalculationsinthe CIE 1976 UCS diagram/ J. Schanda, M. Da ́nyi//ColorRes. Appl. 2, 161–163. –1977.

XVI. Schanda J. Calculating correlated color temperature with a desktop programmable calculator/J. Schanda, M. Me ́sza ́ros, G. Czibula//Color Res. Appl. 3, 65–68. –1978.

XVII. SciPy [Electronicsource]. – Electronic data and programs– Accessmode: http://www.scipy.org/, free. – Accessed date: 21.12.17

XVIII. Wyszecki, G., 1968. Color Science: Concepts and Methods, Quantitative Data and Formulae, pp. 628.

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