Bulletin 3 (32) 2019

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Issue 3 (32) 2019

I. Yermolenko A. V. On the series of conferences «Mathematical modeling and information technology»

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The article is devoted to a series of conferences on mathematical modeling and information technology at the Syktyvkar University. The significance of the conference for the development of science and the involvement of young people in scientific research is substantiated.

Keywords: scientific conference, Syktyvkar, mathematical modeling, information technology.

References

  1. Matematicheskoye modelirovaniye i informatsionnyye tekhnologii : materialy Mezhdunarodnoy nauchnoy konferentsii (Mathematical modeling and information technology: materials of the International Scientific Conference), November 10-11, 2017, Syktyvkar / Ed. A. V. Yermolenko, Syktyvkar: Publishing House of SSU named after Pitirim Sorokin, 2017, 162 p.
  2. Yermolenko A. V. Nauchnaya rabota s Yevgeniyem Il’ichem (Scientific    work with YevgenyIlyich), Bulletin of Syktyvkar University, Series 1: Mathematics. Mechanics. Informatics, 2017, № 3 (24), pp. 4–10.
  3. Mikhailovskii E. I.Shkola mekhaniki akademika Novozhilova (The Novozhilov School of Mechanics). Syktyvkar: Publishing House of the Syktyvkar University, 2005, 172 p.
  4. Chernykh K. F., Mikhailovskii E. I., Nikitenkov V. L. Ob odnoy vetvi nauchnoy shkoly Novozhilova (Novozhilov – Chernykh –Mikhaylovskiy – Nikitenkov) (About one branch of the scientific school of Novozhilov (Novozhilov — Chernykh – Mikhailovsky – Nikitenkov)). Syktyvkar: Publishing House of the Syktyvkar University, 2002, 47 p.
  5. Matematicheskoye modelirovaniye i informatsionnyye tekhnologii: Natsional’naya (Vserossiyskaya) nauchnayakonferentsiya (Mathematical modeling and information technology: materials of the International Scientific Conference), December 6-8, 2018, Syktyvkar / Ed. A. V. Yermolenko, Syktyvkar: Publishing House of SSU named after Pitirim Sorokin, 2018, 161 p.
  6. Matematicheskoye modelirovaniye i informatsionnyye tekhnologii: Natsional’naya (Vserossiyskaya) nauchnaya konferentsiya (National (AllRussian) Scientific Conference), November 7-9, 2019, Syktyvkar: a collection of materials in [Electronic resource]: a textual scientific electronic publication on a CD / rev. ed. A.V. Yermolenko, Syktyvkar: Publishing house of SSU im.Pitirim Sorokin, 2019.1 opt. compact disk (CD-ROM).

For citation:Yermolenko A. V. On the series of conferences «Mathematical modeling and information technology», Bulletin of Syktyvkar University. Series 1: Mathematics. Mechanics. Informatics, 2019, 3 (32), pp. 3–12.

II. Golchevskiy Yu. V., Yermolenko A. V., Kotelina N. O., Osipov D. A. On the series of conferences «Mathematical modeling and information technology»

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About WorldSkills Championship at Syktyvkar University The article describes the experience of the Komi Republic V Open Regional Championship «Young Professionals» (WorldSkills Russia) at the Syktyvkar University.

Keywords: WorldSkills, championship.

For citation:Golchevskiy Yu. V., Yermolenko A. V., Kotelina N. O., Osipov D. A. About WorldSkills Championship at Syktyvkar University, Bulletin of Syktyvkar University. Series 1: Mathematics. Mechanics. Informatics, 2019, 3 (32), pp. 13–19.

III. Belyaeva N. A., Nadutkina A. V. Nonisothermal flow of a viscous fluid

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A mathematical model of the nonisothermal pressure flow of a viscous fluid in a round pipe is considered. The numerical analysis of the dimensionless model is based on the application of the sweep method. Graphical results of numerical experiments are presented.

Keywords: nonisothermal pressure flow, variable viscosity, numerical analysis, sweep method.

References

  1. Belyaeva N. A.Matematicheskoye modelirovaniye: uchebnoye posobiye (Mathematical modeling: a training manual), Syktyvkar: Publishing House of the Syktyvkar State University, 2014, 116 p.
  2. Belyaeva N. A.Osnovy gidrodinamiki v modelyakh: uchebnoye posobiye (Fundamentals of hydrodynamics in models: a training manual), Syktyvkar: Publishing House of the Syktyvkar State University, 2011, 147 p.
  3. KhudyaevS. I. Porogovyye yavleniya v nelineynykh uravneniyakh (Threshold phenomena in nonlinear equations), M.: Fizmatlit, 2003, 272 p.

For citation:Belyaeva N. A., Nadutkina A. V. Non-isothermal flow of a viscous fluid, Bulletin of Syktyvkar University. Series 1: Mathematics. Mechanics. Informatics, 2019, 3 (32), pp. 20–30.

IV. ChernovV. G. Decision making in conditions of uncertainty with fuzzy, linguistic assessments of the situation

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The solution of the decision-making problem is considered under conditions of uncertainty, when the elements of the payment matrix are presented in the form of fuzzy, linguistic statements. A method is proposed for finding the best solution based on a linear order relation on a set of fuzzy integral estimates of alternatives constructed from linguistic estimates.

Keywords:uncertainty, fuzzy set, membership function, fuzzy linguistic estimate, linear order relation.

References

  1. Ventzel E. S.Issledovaniyeoperatsiy. Zadachi, printsipy, metodologiya (Operations research. Tasks, principles, methodology), M.: Drofa, 2004, 208 p.
  2. Seagal A. V.Teoretiko-igrovaya model’ prinyatiya investitsionnykh resheniy (Game-theoretic model of investment decision making), Scientific notes of the Taurida National University named after V.I. Vernadsky, a series of «Economics and Management», v. 24 (63), No. 1, 2011, pp. 193–205.
  3. Vovk S. P.Igradvukhlits s nechetkimistrategiyami i predpochteniyami (A game of two persons with fuzzy strategies and preferences), Almanac of modern science and education, No. 7 (85), pp. 47–49.
  4. Seraya O. V., Katkova T. N.Zadachateoriiigr s nechetkoy platezhnoymatritsey (The task of the theory of games with a fuzzy payment matrix), Mathematical Machines and Systems, 2012, No. 3, pp. 29–36.
  5. Zaichenko Y. P. Igrovyye modeli prinyatiya resheniy v usloviyakh neopredelennosti (Game models of decision making in conditions of uncertainty), Proceedings of the V international school-seminar «Theory of decision-making», Uzhgorod, UzhNU, 2010, 274 p.
  6. Bector C. R., Suresh Chandra. Nechetkoye matematicheskoye programmirovaniye i nechetkiyematrichnyyeigry (Mathematical Programming and Fuzzy Matrix Games), Springer, 2010, 236 p.
  7. Piegat A. Nechetkoye modelirovaniye i upravleniye (Fuzzy modeling and control), M.: BINOM. Laboratoriyaznaniy, 2013, 798 p.
  8. Melikhov A. N., Bernshtein L. S., Korovin S. Y.Situacionnye sovetuyushchiesistemy s nechetkojlogikoj (Situational advisory systems with fuzzy logic), M.: Science, The main edition of the physical and mathematical literature, 1990, 272 p.
  9. Chernov V. G., Andreev I. A., Gradusov D. A., Tretyakov D. V. Resheniyebizneszadach s pomoshch’yunechetkoyalgebry (The solution of business problems by means of fuzzy algebra), M.: TorahCenter, 1998, 87 p.
  10. Chernov V. G. Sravneniye nechetkikh chisel na osnove postroyeniya lineynykh otnosheniy poryadka (Comparison of fuzzy numbers based on the construction of a linear relationship order), Dynamics of complex systems, XXI century2018, No. 2, pp. 81–87.
  11. Chernov V. G.Entropiynyykriteriyprinyatiyaresheniy v usloviyakh polnoyneopredelennosti (Entropy criterion for decision making under conditions of complete uncertainty), Information Management Systems, 6 (7), 2014, pp. 51–56.

For citation: Chernov V. G. Decision making in conditions of uncertainty with fuzzy, linguistic assessments of the situation, Bulletin of Syktyvkar University. Series 1: Mathematics. Mechanics. Informatics, 2019, 3 (32),pp. 31–45.

V. Garbuzov P. A., Gashin R. A. Design, development and implementation of complex automated car fleet management system

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The process of design, development and implementation of complex automated car fleet management system is described. Some problems encountered by the developers and ways to solve them were discussed.

Keywords: complex automated system, car fleet management, MVC architecture, MySQL, PHP.

References

  1. 1C: Predpriyatiye 8. Upravleniye Avtotransportom (1C: Enterprise 8. Car Fleet Management), URL: https://rarus.ru/1c-transport/1c8-avtotransport-standart/ (date of the application: 11.11.2019).
  2. Upravleniye avtotransportom | Kompaniya SIKE (Car Fleet Management | SIKE company), URL: http://autopark.sike.ru/ Bureau of special projects «Bornika» (date of the application: 11.11.2019).
  3. Programma «Avtobaza» – effektivnoye i ekonomichnoye resheniye dlya avtopredpriyatiy (The «Automobile depot» – an effective and economical solution for automobile enterprises), URL: http://www.bornica.ru/autobase/ (date of the application: 11.11.2019).
  4. Upravleniye transportom (TMS) i kur’yerskoy dostavkoy | AllianceSoft (Transport Management (TMS) and courier delivery | AllianceSoft), URL: https://asoft.by/resheniya/upravlenie-transportom-tms-ikurerskoy- dostavkoy (date of the application: 11.11.2019).
  5. Seydametov G. S., Ibraimov R. I. Analiticheskiy obzor shablona MVC (Analytical review of the MVC template), Informatsionnokomp’yuternyyetekhnologii v ekonomike, obrazovanii i sotsial’noysfere, 2018, No. 3 (21), pp. 45–51.
  6. Belykh E. A., Golchevskiy Yu. V. Podkhod k proyektirovaniyu yazyka podstanovok dlya generatsii elektronnykh dokumentov, soderzhashchikh slozhnyye tablitsy (An approach to designing a substitution language for generating electronic documents containing complex tables), VestnikUdmurtskogouniversiteta. Matematika.Mekhanika. Komp’yuternyyenauki, 2019, vol. 29, issue 3, pp. 422–437. DOI: 10.20537 / vm190311.

For citation: Garbuzov P. A., Gashin R. A. Design, development and implementation of complex automated car fleet management system, Bulletin of Syktyvkar University. Series 1: Mathematics. Mechanics. Informatics, 2019, 3 (32), pp. 46–61.

VI. Nosov L. S., Pipunyrov E. Y.  Stream encryption based on FPGA

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It is proposed to use a soft-processor, which described in Verilog language, and FPGA to create a universal stream cipher, which could be programmed and quickly adapted at the hardware level.

Keywords: information security, FPGA, stream cipher.

References

  1. P. Pal Chaudhuri. Computer organisation and design, Delhi: PHI Learning, 2014, 897 p.
  2. David M. Harris and Sarah L. Harris. Digital Design and Computer Architecture, Boston: Morgan Kaufman, 2007, 570 p.
  3. GOST R 34.12-2015 Informatsionnayatekhnologiya. Kriptograficheskayazashchitainformatsii. Blochnyyeshifry (Information technology. Cryptographic information security. Block ciphers), M.: Standartinform, 2015, 25 p.
  4. IEEE 1364-2001 IEEE Standard Verilog Hardware Description Language. USA: The Institute of Electrical and Electronics Engineers, 2001, 778 p.
  5. Pong P. Chu. FPGA prototyping by Verilog examples Xilinx Spartan-3 Version. New Jersey:John Wiley & Sons, 2008, 488 p.
  6. Spartan-3A/3AN FPGA Starter Kit Board User Guidei. v. 1.1.XILINX, 2008, 140 p.
  7. SamodelovА. Kriptografiya v otdel’nom bloke: kriptograficheskiy soprotsessor semeystva STM32F4xx. Ofitsial’nyysaytkompanii «Kompel» (Cryptography in a separate block: cryptographic coprocessorSTM32F4xx family. The official website of the company «Kompel»),URL: http: //www.compel.ru/lib/ne/2012/6/4-kriptografiya-votdelnom-bloke-kriptograficheskiy-so-protsessor-semeystva-stm32f4xx.(date of the application: 03.12.2016).

For citation: Nosov L. S., Pipunyrov E. Y. Stream encryption based onFPGA, Bulletin of Syktyvkar University. Series 1: Mathematics. Mechanics. Informatics, 2019, 3 (32), pp. 62–76.

VII. Dorofeev S. N., Nazemnova N. V. Methodological features of teaching high school students to recognize geometric images

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The article deals with the problem of teaching students to recognize geometric images. It is noted that this quality in the process of learning geometry has a personality-oriented character, the fact that learning to recognize geometric images will be most effective if you use the activity approach is substantiated.Keywords:teaching mathematics, recognition of geometric images, activity approach, vector-coordinate method, teaching students the discovery of «new» knowledge.

References

  1. 1. Ananyev B. G. Psikhologiyachuvstvennogopoznaniya (Psychologyof sensory cognition), M, 1960, 488 p.
  2. Ananyev B. G. Novoye v uchenii o vospriyatiiprostranstva (New in the doctrine of perception of space), Questions of psychology, 1960, No 1, pp. 18–29.
  3. Borodai Yu. M. Voobrazheniye i teoriyapoznaniya (Imagination and theory of knowledge), M, 1966, 192 p.
  4. Dorofeev S. N. Trudnosti metodiki obucheniya resheniyu zadach vektornym metodom i putiikhpreodoleniya (Difficulties of teaching methods to solve problems by vector method and ways to overcome them), Materials of interregional scientific and practical conference, Penza, 1997, pp. 389–390.
  5. Nazemnova N. V. Mnogokomponentnoye uprazhneniye kak sredstvo formirovaniya u uchashchikhsya deystviyaporaspoznavaniyuobraza (Multicomponent exercise as a means of forming students ’ actions on image recognition), University education: sat. nauch. works submitted to the international exhibition. science.-method.Conf. Penza: Privolzhsky house of knowledge, MKUO, 2004, pp. 326–329. 

For citation: Dorofeev S. N., Nazemnova N. V. Methodological features of teaching high school students to recognize geometric images, Bulletin of Syktyvkar University. Series 1: Mathematics. Mechanics. Informatics, 2019, 3 (32), pp. 77–88.

VIII. Mansurova E. R., Nizamova E. R. Generalization in analysis as a means of improving the quality of mathematical preparation of students

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The article considers the role of generalization in analysis in improving the level of mathematical training of secondary school students on the example of the topic «Primitive and integral». Tasks on the topic are presented from textbooks on algebra and the principles of analysis currently used in the school course in mathematics, as well as from didactic materials for specialized classes and materials of the exam.Keywords: generalization, analysis, school, profile, integral, antiderivative, derivative, function, USE.

References

  1. Davydov V. V. Vidyobobshcheniya v obuchenii (Types of generalization in learning), M.: Pedagogical Society of Russia, 2000, pp. 157–173.
  2. Kolyagin Yu. M. Metodika prepodavaniya matematiki v sredney shkole. Obshchaya metodika (Methods of teaching mathematics in high school), General technique. Cheboksary: Publishing house of Chuvash. Univ., 2009, pp. 86–95.
  3. Sawyer W. W. Prelyudiya k matematike (Prelude to mathematics), M.: Education, 1972, pp. 37–47.
  4. Prozorovskaya S. D., Filipova T. I., Kropacheva N. Yu. Formirovaniye osnovnykh ponyatiy matematicheskogo analiza na osnove teoreticheskogoobobshcheniya (Formation of the basic concepts of mathematical analysis based on theoretical generalization), Siberian Pedagogical Journal, 2012, № 8, pp. 88–92.
  5. Pratusevich M. Ya. Algebra i nachala matematicheskogo analiza. 11 klass (Algebra and the beginning of mathematical analysis, Grade 11), M.: Education, 2010, 463 p.
  6. Nathanson I. P. Teoriya funktsiy veshchestvennoy peremennoy (The theory of functions of a real variable), St. Petersburg: Doe, 2018, 560 p.
  7. Merzlyak A. G. Algebra. 11 klass (Algebra. Grade 11), Kharkov: Gymnasium, 2011, 431 p.
  8. Muravin G. K. Algebra i nachala matematicheskogo analiza. 11 kl (Algebra and the beginning of mathematical analysis. 11 cl), M.: Bustard, 2013,253 p.
  9. Ryzhik V. I. Didakticheskiye materialy po algebre i matematicheskomu analizu dlya 10-11 klassov (Didactic materials on algebra and mathematical analysis for grades 10-11), M.: Education, 1997, 144 p.
  10. Mordkovich A. G. Algebra i nachala analiza. 10 kl (Algebra and the beginning of analysis. 10 cl), M.: Mnemozina, 2009, 443 p.
  11. Mordkovich A. G. Algebra i nachala analiza. 10-11 kl (Algebra and the beginning of analysis. 10-11 cl), Ch. 2, M.: Mnemozina, 2003, 315 p.
  12. Nikolsky S. M. Algebra i nachala matematicheskogo analiza. 11 klass (Algebra and the beginning of mathematical analysis, Grade 11), M.: Education, 2009, 446 p.
  13. Reshu YEGE (I will solve the Unified State Exam) [Electronic resource]. URL: https://math-ege.sdamgia.ru/test?theme=183 (accessed 11.15.19).
  14. ALEXLARIN.NET [Electronic resource]. URL: http://alexlarin.net/
  15. ege20.html (accessed 11.15.19).

For citation: Mansurova E. R., Nizamova E. R. Generalization in analysis as a means of improving the quality of mathematical preparation of students, Bulletin of Syktyvkar University. Series 1: Mathematics. Mechanics. Informatics, 2019, 3 (32), pp. 89–100.

IX. Kotelina N. O., Matwiichuck B. R. Image clustering by k-means

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The paper deals with the problem of data clustering by the k-means method on the example of a raster image. The solution of the problem will be a program that implements the k-means method and as a result of the work, produces images divided into k clusters. The quality of clustering is estimated.Keywords: k-means method, clustering, cluster.

References

  1. Kotov A., Krasilnikov N. Klasterizatsiyadannykh (Data clustering), M., 2006, 16 p.
  2. Chubukova I. A. Data Mining, M.: Binom, 2008, 326 p.
  3. Obzor algoritmov klasterizatsii dannykh (Overview of data clustering algorithms), URL: tt https://habr.com/en/post/101338/ (date of theapplication: 12.02.2019).
  4. Tyurin A. G., Zuev I. O. Klasternyyanaliz, metody i algoritmyklasterizatsii (Cluster analysis, methods and algorithms of clustering), Vestnik MGTU MIREA, No 12, M.: Publishing house of MSTU, 2014,12 p.
  5. Ian Eric Solem Programmirovaniye komp’yuternogo zreniya na yazyke Python (Programming computer vision in Python), M.: DMK
  6. Press, 2016, 312 p.

For citation: Kotelina N. O., Matwiichuck B. R. Image clustering by kmeans, Bulletin of Syktyvkar University. Series 1: Mathematics. Mechanics.Informatics, 2019, 3 (32), pp. 101–112.

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