Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 31
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

Study of the trajectories of the motion of satellites remains an urgent task for modern science. This is especially true for GNSS systems and for satellites intended for Earth remote sensing. The basis of their operation is to accurately determine the position of the satellite, and the parameters of signal propagation. Considering the great distances and speeds of both satellites and the Earth in calculating these parameters, it is necessary to take into account the special and general theory of relativity. In the article formulas have been derived for calculating additional corrections for relativistic effects. A mathematical model for calculating the metric tensor was created. A sequence of correction was also proposed.
Go to article

Authors and Affiliations

Waldemar Wójcik
Ihor Bialyk
Olha Stepanchenko
Download PDF Download RIS Download Bibtex

Abstract

The article describes methods of user identification using authentication based on the second factor. Known algorithms and protocols for two-factor authentication are considered. An algorithm is proposed using mobile devices as identifiers and generating a temporary password based on the hash function of encryption standards. For an automated control system, a two-factor authentication model and a sequential algorithm for generating a temporary password using functions have been developed. The implementation of the system is based on the Node.js software platform using the JavaScript programming language, as well as frameworks and connected system libraries. MongoDB, an open source database management system for information storage and processing was used.
Go to article

Bibliography

1] D. R. Yuryev and O. S. Rogova, “Comparative analysis of two-factor authentication”, Proc. of Int. Conference Technical sciences - from theory to practice to mater SibAK2017, Novosibirsk, 2017, pp.46–51.
[2] Transfer of Customer Details OAuth, (2019, May) [Online], Available: https://www.ibm.com/ developerworks/ru/library/se-oauthjavapt2/index.html
[3] HMAC: Keyed-Hashing for Message Authentication, (2019, May) [Online], Available: https://tools.ietf.org/ html/rfc2104
[4] N. Moretto. (2019, Aug). Two-factor authentication with TOTP, Available: https://medium.com/@n.moretto/two-factor-authentication-with-totp-ccc5f828b6df
[5] O. Ussatova, S. Nyssanbayeva and W. Wójcik, “Development of an authentication model based on the second factor in an automated control system,” KBTU News, vol. 16, pp. 115–118, 2019.
[6] S. Nysanbayeva, W. Wojcik and O. Ussatova, “Algorithm for generating temporary password based on the two-factor authentication model,” Przegląd Elektrotechniczny 5(R95), pp. 101–106, 2019.
[7] Two-factor authentication, (2019, Aug) [Online]. Available: https://www.infobip.com/ru/glossariy/dvukhfaktornaya-autentifikatsiya (last accessed September 07, 2019 y.).
[8] FIPS 140-2 standard and self-encryption technology. (2018, Sep) [Online]. Available: https://www.seagate.com/files/www-content/solutions-content/security-and-encryption/id/docs/faq-fips-sed-lr- mb-605-2-1302-ru.pdf
[9] National Security Agency. (2018, Jun). [Online]. Available: https://www.cryptomuseum.com/intel/nsa/index.htm
[10] O. Ussatova and S. Nyssanbayeva, “Generators of one-time two-factor authentication passwords,” Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, no. 2(R71), pp. 60–64, 2019.
[11] MongoDB Tutorial. (2019, Sep) [Online]. Available: https://www. tutorialspoint.com/mongodb/index.htm
[12] O. Ussatova, S. Nyssanbayeva and W. Wójcik, “Two-factor authentication algorithm implementation with additional security parameter based on mobile application,”, Proc. on International Conference on Wireless Communication, Network and Multimedia Engineering (WCNME2019), Guilin, 2019, pp. 84–86.
[13] O. Ussatova, S. Nyssanbayeva and W. Wójcik, “Software implementation of two-factor authentication to ensure security when accessing an information system,” News of KazNU im. al-Farabi, 136, pp. 87–95, March 2019.
Go to article

Authors and Affiliations

Olga Ussatova
1 2
Saule Nyssanbayeva
2
Waldemar Wójcik
3

  1. Al-Farabi Kazakh National University, Almaty, Kazakhstan
  2. Institute of Information and Computational Technologies, Almaty, Kazakhstan
  3. Lublin University of Technology, Nadbystrzycka 38a, 20-618 Lublin
Download PDF Download RIS Download Bibtex

Abstract

In this article, a monitoring system based on IoT technologies of the substation electrical system in the Republic of Kazakhstan was developed. At the moment, the operation of power systems is extremely important to maintain the frequency of electric current over time. For management and monitoring applications, it is necessary to take into account communication within acceptable limits. IoT technologies are considered the main functions in applications for monitoring and managing energy systems in real time, as well as making effective decisions on both technical and financial issues of the system, for monitoring the main form of data registration on an electric power substation in the city of Shymkent of the Republic of Kazakhstan, for consistent effective decision-making by system operators. In this work, an Internet of Things-based monitoring system was implemented and implemented for the substation of the power system using a specialized device built into the FPGA controller for fast integrated digitalization of transformer substations of real-time distribution electrical networks. The IoT platform also provides complete remote observability and will increase reliability for power system operators in real time. This article is mainly aimed at providing a practical application that has been implemented and tested.
Go to article

Authors and Affiliations

Maksat Kalimoldayev
1
Waldemar Wójcik
2
Zhazira Shermantayeva
1

  1. Institute ofInformation and Computing Technologies of the KN of the Ministry ofInternal Affairs of the Republic of Kazakhstan
  2. Lublin University of Technology, Lublin, Poland
Download PDF Download RIS Download Bibtex

Abstract

A significant threat to critical infrastructure of computer systems has a destructive impact caused by infrasound waves. It is shown that the known infrasound generations are based on using the following devices: a Helmholtz Resonator, Generation by using a Pulsating Sphere such as Monopolies, Rotor-type Radiator, Resonating Cylinder, VLF Speaker, Method of Paired Ultrasound Radiator, and airscrew. Research of these devices was made in this paper by revealing their characteristics, main advantages and disadvantages. A directional pattern of infrasound radiation and a graph of dependence of infrasound radiation from the consumed power was constructed. Also, during the analysis of these devices, there was proven a set of basic parameters, the values of which make it possible to characterize their structural and operational characteristics. Then approximate values of the proposed parameters of each those considered devices, were calculated. A new method was developed for evaluating the effectiveness of infrasound generation devices based on the definition of the integral efficiency index, which is calculated using the designed parameters. An example of practical application of the derived method, was shown. The use of the method makes it possible, taking into account the conditions and requirements of the infrasound generation devices construction, to choose from them the most efficient one.
Go to article

Authors and Affiliations

Waldemar Wójcik
Alexander Korchenko
Igor Tereykovsky
Evgenia Aytkhozhaevа
Seilova Nurgul
Yevgeny Kosyuk
Paweł Komada
Jan Sikora
Download PDF Download RIS Download Bibtex

Abstract

The operating modes of the automatic control system for electromechanical converters for synchronization of rotor speeds have been developed and investigated. The proposed automatic speed control system allows adjusting the slave engine to the master one in a wide range from 0 to 6000 rpm. To improve the synchronization accuracy an adaptive algorithm is proposed that allows to increase the synchronization accuracy by 3-4 times. The proposed model of an adaptive automatic control system with an observing identification tool makes it possible to minimize the error in the asynchrony of the rotation of the rotors of two electromechanical converters.
Go to article

Authors and Affiliations

Aidana Kalabayeva
1 2
Waldemar Wójcik
3
Gulzhan Kashaganova
4
Kulzhan Togzhanova
5
Zhaksygul Sarybayeva
1

  1. Academy of Logistics and Transport, Almaty, Kazakhstan
  2. Almaty University of Power Engineering and Telecommunications Almaty, Kazakhstan
  3. Lublin University of Technology, Lublin, Poland
  4. Turan University, Almaty, Kazakhstan
  5. Almaty Technological University, Almaty, Kazakhstan
Download PDF Download RIS Download Bibtex

Abstract

An article herein presents an optimization model, designated for computational core of decision-taking support system (DTSS). DTSS is necessary for system analysis and search of optimal versions for cyber security facilities placement and information protection of an enterprise or organization distributed computational network (DCN). DTSS and a model allow automize the analysis of information protection and cyber security systems in different versions. It is possible to consider, how separate elements, influence at DCN protection factors and their combinations. Offered model, in distinction from existing, has allowed implementing both the principles of information protection equivalency to a concrete threat and a system complex approach to forming a highly effective protection system for DCN. Hereby we have presented the outcomes of computational experiments on selecting the rational program algorithm of implementing the developed optimization model. It has been offered to use genetic algorithm modification (GAM). Based on the offered model, there has been implemented the module for adaptive DTSS. DTSS module might be applied upon designing protected DCN, based on preset architecture and available sets of information protection and cyber security systems in the network.

Go to article

Authors and Affiliations

Aliya Kalizhanova
Sultan Akhmetov
Valery Lakhno
Waldemar Wójcik
Gulnaz Nabiyeva
Download PDF Download RIS Download Bibtex

Abstract

The article is devoted to some critical problems of using Bayesian networks for solving practical problems, in which graph models contain directed cycles. The strict requirement of the acyclicity of the directed graph representing the Bayesian network does not allow to efficiently solve most of the problems that contain directed cycles. The modern theory of Bayesian networks prohibits the use of directed cycles. The requirement of acyclicity of the graph can significantly simplify the general theory of Bayesian networks, significantly simplify the development of algorithms and their implementation in program code for calculations in Bayesian networks..
Go to article

Bibliography

[1] A. Nafalski and A.P. Wibawa, “Machine translation with javanese speech levels’ classification,” Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, vol. 6, no 1, pp 21-25, 2016. https://doi.org/10.5604/20830157.1194260
[2] Z.Omiotek and P. Prokop, “The construction of the feature vector in the diagnosis of sarcoidosis based on the fractal analysis of CT chest images,” Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, vol. 9, no. 2, pp. 16-23, 2019. https://doi.org/10.5604/01.3001.0013.2541
[3] A. Litvinenko, O. Mamyrbayev, N. Litvinenko, A. Shayakhmetova, “Application of Bayesian networks for estimation of individual psychological characteristics,” Przeglad Elektrotechniczny, vol. 95, no. 5, pp. 92-97, 2019
[4] X.Q. Cai, X.Y. Wu, X. Zhou, “Stochastic scheduling subject to breakdown-repeat breakdowns with incomplete information,” Operations Research, vol. 57, no. 5, pp. 1236–1249, 2009. doi: 10.1287/opre.1080.0660
[5] K.W. Fornalski, “The Tadpole Bayesian Model for Detecting Trend Changes in Financial Quotations,” R&R Journal of Statistics and Mathematical Sciences, vol. 2, no. 1, pp. 117–122, 2016.
[6] J. Pearl “Artificial Intelligence Applications”, in How to Do with Probabilities what people say you can't,/ Editor Weisbin C.R., IEEE, North Holland, pp. 6–12, 1985.
[7] J. Pearl “Probabilistic Reasoning in Intelligent Systems”. San Francisco: Morgan Kaufmann Publishers, 1988,
[8] A. Tulupiev “Algebraic Bayesian networks,” in “Logical-probabilistic approach to modeling knowledge bases with uncertainty,” SPb.: SPIIRAS, 2000.
[9] S. Nikolenko, A. Tulupiev “The simplest cycles in Bayesian networks: Probability distribution and the possibility of its contradictory assignment,” SPIIRAS. Edition 2, 2004. vol.1.
[10] F.V. Jensen, T.D. Nielsen “Bayesian Networks and Decision Graphs,” Springer, 2007.
[11] D. Barber, “Bayesian Reasoning and Machine Learning,” 2017, 686 p. http://web4.cs.ucl.ac.uk/ staff/D.Barber/ textbook/020217.pdf
[12] R.E. Neapolitan “Learning Bayesian Networks,” 704p. http://www.cs.technion.ac.il/~dang/books/Learning%20Bayesian%20Networks(Neapolitan,%20Richard).pdf
[13] O. Mamyrbayev, M. Turdalyuly, N. Mekebayev, and et al. “Continuous speech recognition of kazakh language», AMCSE 2018 Int. conf. On Applied Mathematics, Computational Science and Systems Engineering, Rom, Italy, 2019, vol. 24, pp. 1-6.
[14] A. Litvinenko, N. Litvinenko, O. Mamyrbayev, A. Shayakhmetova, M. Turdalyuly “Clusterization by the K-means method when K is unknown,” Inter. Conf. Applied Mathematics, Computational Science and Systems Engineering. Rome, Italy, 2019, vol. 24, pp. 1-6.
[15] O.Ore “Graph theory,” Мoscow: Science, 1980, 336 p.
[16] Ph. Kharari “Graph theory,” Мoscow: Mir, 1973, 300 p.
[17] V. Gmurman “Theory of Probability and Mathematical Statistics: Tutorial,” Moscow: 2003, 479 p.
[18] A.N. Kolmogorov “Theory: Manual,” in “Basic Concepts of Probability,” Moscow: Science, 1974.
[19] N. Litvinenko, A. Litvinenko, O. Mamyrbayev, A. Shayakhmetova “Work with Bayesian Networks in BAYESIALAB,” Almaty: IPIC, 2018, 311 p. (in Rus). ISBN 978-601-332-206-3.

Go to article

Authors and Affiliations

Assem Shayakhmetova
1 2
Natalya Litvinenko
3
Orken Mamyrbayev
1
Waldemar Wójcik
4 5
Dusmat Zhamangarin
6

  1. Institute of Information and Computational Technology, 050010 Almaty, Kazakhstan
  2. Al-Farabi Kazakh National University, Almaty, Kazakhstan
  3. Information and Computational Technology, 050010 Almaty, Kazakhstan
  4. Institute of Information and Computational Technologies CS MES RK, Almaty
  5. Lublin Technical University, Poland
  6. Kazakh University Ways of Communications, Kazakhstan
Download PDF Download RIS Download Bibtex

Abstract

Assessment of seismic vulnerability of urban infrastructure is an actual problem, since the damage caused by earthquakes is quite significant. Despite the complexity of such tasks, today’s machine learning methods allow the use of “fast” methods for assessing seismic vulnerability. The article proposes a methodology for assessing the characteristics of typical urban objects that affect their seismic resistance; using classification and clustering methods. For the analysis, we use kmeans and hkmeans clustering methods, where the Euclidean distance is used as a measure of proximity. The optimal number of clusters is determined using the Elbow method. A decision-making model on the seismic resistance of an urban object is presented, also the most important variables that have the greatest impact on the seismic resistance of an urban object are identified. The study shows that the results of clustering coincide with expert estimates, and the characteristic of typical urban objects can be determined as a result of data modeling using clustering algorithms.
Go to article

Bibliography

[1] I. Riedel, Ph. Guéguen, M. D. Mura, E. Pathier, T. Leduc, J. Chanussotet, “Seismic vulnerability assessment of urban environments in moderate-to-low seismic hazard regions using association rule learning and support vector machine methods”, Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer, vol. 76, no. 2, March 2015, pp. 1111-1141, DOI: 10.1007/s11069-014-1538-0.
[2] Z. Zhang, T.-Y. Hsu, H.-H. Wei, J.-H. Chen, “Development of a Data-Mining Technique for Regional-Scale Evaluation of Building Seismic Vulnerability,” Applied Sciences, vol. 9, no. 7, April 2019, p. 1502, DOI: 10.3390/app9071502.
[3] C. S. Chen, M. Y. Cheng, Y. W. Wu, “Seismic assessment of school buildings in Taiwan using the evolutionary support vector machine inference system,” Expert Systems with Applications, vol. 39, no. 4, March 2012, pp. 4102-4110, DOI: 10.1016/j.eswa.2011.09.078.
[4] H. M. Chen, W. K. Kao, H. C. Tsai, “Genetic programming for predicting aseismic abilities of school buildings,” Engineering Applications of Artificial Intelligence, vol. 25, no. 6, Sep. 2012, pp. 1103-1113, DOI: 10.1016/j.engappai.2012.04.002
[5] W. K. Kao, H. M. Chen, J. S. Chou, “Aseismic ability estimation of school building using predictive data mining models,” Expert Systems with Applications, vol. 38, Aug. 2011, pp. 10252-10263, DOI: 10.1016/j.eswa.2011.02.059.
[6] Y. Liu, Z. Li, B. Wei, Xiaoli li, “Seismic vulnerability assessment at urban scale using data mining and GIScience technology: application to Urumqi (China),” Geomatics, Natural Hazards and Risk, vol. 10, no. 1, Jan. 2019, pp. 958-985, DOI: 10.1080/19475705.2018.1524400.
[7] X. Shang, Xibing Li, A. Morales-Esteban, G. A. Cortés, “Data field-based K-means clustering for spatio-temporal seismicity analysis and hazard assessment”, Remote Sensing, vol. 10, no. 3, March 2018, p. 461, DOI:10.3390/rs10030461.
[8] J. Ortega, G. Vasconcelos, H. Rodrigues, M. Correia, “Development of a Numerical Tool for the Seismic Vulnerability Assessment of Vernacular Architecture”, Journal of Earthquake Engineering, pp. 1-29, Sep. 2019, DOI: 10.1080/13632469.2019.1657987.
[9] G. Brando, G. De Matteis, E. Spacone, “Predictive model for the seismic vulnerability assessment of small historic centres: application to the inner Abruzzi Region in Italy”, Engineering Structures, vol. 153, Dec. 2017, pp. 81-96, DOI: 10.1016/j.engstruct.2017.10.013.
[10] C. Drago, R. Ferlito, M. Zucconiс, “Clustering of damage variables for masonry buildings measured after L’Aquila earthquake,” Sep. 2015.
[11] E. Irwansyah, Е. Winarko, “Spatial data clustering and zonation of earthquake building damage hazard area,” The European Physical Journal Conferences, 68. Feb. 2014. DOI: 10.1051/epjconf/20146800005.
[12] A. Guettiche, Ph. Gueguen, “Seismic vulnerability assessment using association rule learning: application to the city of Constantine, Algeria,” Natural Hazards, vol. 86 no. 3, Jan. 2017. doi: 10.1007/s11069-016-2739-5.
[13] I. Riedel, P. Gueguen, F. Dunand, S.Cottaz, “Macroscale vulnerability assessment of cities using association rule learning,” Seismol Res Lett, vol. 85, no. 2, pp. 295–305, 2014.
[14] D. P. Sari, D. Rosadi, A. R. Effendie, D. Danardono, “Application of Bayesian network model in determining the risk of building damage caused by earthquakes,” in 2018 International Conference on Information and Communications Technology, January 2018, pp. 131-135.
[15] D. P. Sari, D. Rosadi, A. R. Effendie, D. Danardono, “K-means and bayesian networks to determine building damage levels,” Computer Science, vol. 17, no. 2, pp. 719–727, April 2019. DOI: 10.12928/telkomnika.v17i2.11756.
[16] R. Zhang, Zh. Chen, S. Chen, J. Zheng, O. Büyüköztürk, H. Sun, “Deep long short-term memory networks for nonlinear structural seismic response prediction,” Computers & Structures, pp. 55-68, Aug. 2019.
[17] V. N. Kasyanov, V. A. Evstigneev, “Graphs in programming: processing, visualization and application,” SPb.: BHV-Petersburg, 2003.
[18] P. J. Tan, D. L. Dowe, “MML inference of decision graph with milti-way and dynamic attributes,” http://www.csse.monash.edu.au/~dld/ Publications/2003/Tan+Dowe2003_MMLDecisionGraphs.pdf.
[19] L. Breiman, “Random forests,” Machine Learning, vol. 45, no. 1, pp. 5-32, 2001.
[20] T. Hastie, R. Tibshirani, J. Friedman, “Chapter 15. Random Forests,” in The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer-Verlag, 2009.
[21] M. Pal, “Random forest classifier for remote sensing classification,” International Journal of Remote Sensing, vol. 26, no. 1, pp. 217–222, 2015.
[22] M. Karmenova, A. Nugumanova, A. Tlebaldinova. “Klasternyy analiz dannykh v reshenii zadach po otsenke seysmicheskoy uyazvimosti ob’yektov gorodskoy sredy,” Scientific and technical journal «Vestnik AUES», vol. 1, no. 48, 2020.
[23] M. Karmenova, A. Nugumanova, A. Tlebaldinova, A. Beldeubaev, G. Popova, A. Sedchenko, “Seismic assessment of urban buildings using data mining methods,” ICCTA’20, April 2020, pp 154–159. DOI: 10.1145/3397125.3397152.
[24] L. Breiman, R. Friedman, R. Olshen, C. Stone. “Classification and Regression Trees,” Belmont, California: Wadsworth International, 1984.
[25] J. R. Quinlan, “Simplifying decision trees,” International Journal of ManMachine Studies, vol. 27, pp. 221–234, 1987.
[26] C. P. Chistyakov, “Random forests: an overview,” Proceedings of the Karelian scientific center of the Russian Academy of Sciences, no. 1, pp. 117-136, 2013.
[27] V.F. Rodriguez-Galiano, B. Ghimire, J. Rogan, M. Chica-Olmo, J. P. Rigol-Sanchez, “An assessment of the effectiveness of a random forest classifier for land-cover classification,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 67, pp. 93-104, Jan 2012.
[28] R. Dzierżak, “Comparison of the influence of standardization and normalization of data on the effectiveness of spongy tissue texture classification,” Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, vol. 9, no. 3, pp. 66-69, Mar. 2019. https://doi.org/10.35784/iapgos.62
[29] Otchet po vyborochnomu obsledovaniyu zdaniy v ramkakh «Issledovaniya po upravleniyu riskami, svyazannymi s seysmicheskimi bedstviyami v gorode Almaty, Respublika Kazakhstan», Almaty, Feb. 2008. https://openjicareport.jica.go.jp/pdf/11961802_02.pdf.

Go to article

Authors and Affiliations

Waldemar Wójcik
1
Markhaba Karmenova
2
Saule Smailova
2
Aizhan Tlebaldinova
3
Alisher Belbeubaev
4

  1. Lublin Technical University, Poland
  2. D. Serikbayev East Kazakhstan State Technical University, Kazakhstan
  3. S. Amanzholov East Kazakhstan State University, Kazakhstan
  4. Cukurova University, Turkey
Download PDF Download RIS Download Bibtex

Abstract

This paper investigates the possibility of automatically linearizing nonlinear models. Constructing a linearised model for a nonlinear system is quite labor-intensive and practically unrealistic when the dimension is greater than 3. Therefore, it is important to automate the process of linearisation of the original nonlinear model. Based on the application of computer algebra, a constructive algorithm for the linearisation of a system of non-linear ordinary differential equations was developed. A software was developed on MatLab. The effectiveness of the proposed algorithm has been demonstrated on applied problems: an unmanned aerial vehicle dynamics model and a twolink robot model. The obtained linearized models were then used to test the stability of the original models. In order to account for possible inaccuracies in the measurements of the technical parameters of the model, an interval linearized model is adopted. For such a model, the procedure for constructing the corresponding interval characteristic polynomial and the corresponding Hurwitz matrix is automated. On the basis of the analysis of the properties of the main minors of the Hurwitz matrix, the stability of the studied system was analyzed.
Go to article

Authors and Affiliations

Aigerim Mazakova
3
Sholpan Jomartova
3
Waldemar Wójcik
2
Talgat Mazakov
1
Gulzat Ziyatbekova
1

  1. Institute of Information and Computational Technologies CS MES RK, Al-Farabi Kazakh National University, Kazakhstan
  2. Lublin Technical University, Poland
  3. Al-Farabi Kazakh NationalUniversity, Kazakhstan
Download PDF Download RIS Download Bibtex

Abstract

This paper is focused on multiple soft fault diagnosis of linear time-invariant analog circuits and brings a method that achieves all objectives of the fault diagnosis: detection, location, and identification. The method is based on a diagnostic test arranged in the transient state, which requires one node accessible for excitation and two nodes accessible for measurement. The circuit is specified by two transmittances which express the Laplace transform of the output voltages in terms of the Laplace transform of the input voltage. Each of these relationships is used to create an overdetermined system of nonlinear algebraic equations with the circuit parameters as the unknown variables. An iterative method is developed to solve these equations. Some virtual solutions can be eliminated comparing the results obtained using both transmittances. Three examples are provided where laboratory or numerical experiments reveal effectiveness of the proposed method.
Go to article

Bibliography

[1] A. Guney, G. Önal and T. Atmaca, “New aspect of chromite gravity tailings re-processing”, Minerals Engineering, Vol., 24, no 11, pp. 1527- 1530, 2001. https://doi.org/10.1016/S0892-6875(01)00165-0.
[2] W.M. Ambrósa, C.H. Sampaioa, Bogdan G. Cazacliub, Paulo N.Conceiçãoa and Glaydson S.dos Reisab, “Some observations on the influence of particle size and size distribution on stratification in pneumatic jigs”, Powder Technology, Vol. 342, pp. 594-606, 2019. https://doi.org/10.1016/j.powtec.2018.10.029.
[3] M.V. Verkhoturov, “Gravitational enrichment methods”. Moscow: MAX Press, 2006, pp.160- 180. ISBN 5-317-01710-6.
[4] Ya-li Kuang, Jin-Wu Zhuo, Li Wang, Chao Yang, “Laws of motion of particles in a jigging process”, Journal of China University of Mining and Technology, Vol. 18, no 4, pp. 575-579, December 2008. https://doi.org/10.1016/S1006-1266(08)60297-7.
[5] S.Cierpisz. “A dynamic model of coal products discharge in a jig”, Minerals Engineering, Vol. 105, pp. 1-6, 1 May 2017. https://doi.org/10.1016/j.mineng.2016.12.010.
[6] B.A. Suleimenov and Ye.A. Kulakova, “The prospects for the use of intelligent systems in the processes of gravitational enrichment”, Informatyka, Automatyka, Pomiary w Gospodarcei Ochronie Środowiska, Vol. 9, no 2, pp. 46-49, 2019. https://doi.org/10.5604/01.3001.0013.2547.
[7] Y.R. Murthy, S.K. Tripathy, C.R. Kumar, “Chrome ore beneficiation challenges & opportunities – A review”, Minerals Engineering, Vol. 24, no 5, pp. 375-380, 2011, DOI: https://doi.org/10.1016/j.mineng.2010.12.001.
[8] L. Panda, S.K. Tripathy, “Performance prediction of gravity concentrator by using artificial neural network – A case study”. International Journal of Mining Science and Technology, Vol. 24, no 4, pp. 461-465, 2014. https://doi.org/10.1016/j.ijmst.2014.05.007.
[9] Y.R. Murthy, S.K. Tripathy, C.R. Kumar, “Chrome ore beneficiation challenges & opportunities-a review”, Minerals Engineering, Vol. 36, no 5, pp. 375-380, 2014, https://doi.org/10.1016/j.ijmst.2014.05.007.
[10] T. J. Stich, and J.K. Spoerre and T.Velasco, “The application of artificial neutral networks to monitoring and control of an induction hardening process”, Journal of Industrial Technology, Vol. 16, no 1, pp.168-174, 2015.
[11] L.Panda, A.K. Sahoo, S.K Tripathy and others, “Application of artificial neural network to study the performance of jig for beneficiation of noncoking coal”, Fuel, Vol. 97, pp. 151-156, 2012. https://doi.org/10.1016/j.fuel.2012.02.018.
[12] K. Shravan and R. Venugopal, “Performance analyses of jig for coal cleaning using 3D response surface methodology”, International Journal of Mining Science and Technology, Vol. 27, no 2, pp 333-337, March 2017.
[13] B.A. Suleimenov and E.A. Kulakova, “Development of intelligent system for optimal process control”, Resource–saving technologies of raw–material base development in mineral mining and processing: Multy–authored monograph, Universitas Publishing, Romania, Petrosani: 2020, pp.198-217. URI: ep3.nuwm.edu.ua/id/eprint/18359.
[14] V. Mashkov, A. Smolarz, V. Lytvynenko, and K. Gromaszek, “The problem of system fault-tolerance”, Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, vol. 4, no. 4, pp. 41-44, 2014, https://doi.org/10.5604/20830157.1130182
[15] M. S. Islam, P. Nepal and others. “A knowledge-based expert system to assess power plant project cost overrun risks”, Expert Systems With Applications, Vol. 136, pp. 12-32, 2019. https://doi.org/10.1016/j.eswa.2019.06.030.
[16] B.A.Suleimenov and E.A Kulakova, “Creation the knowledge base of the intelligent control system for gravitational enrichment processes using expert information processing methods”, Vestnik KazNRTU, Vol. 5, no 141, pp. 590-597, October 2020.
[17] Ye.A. Kulakova and B.A. Suleimenov, “Development and Research of Intelligent Algorithms for Controlling the Process of Ore Jigging”, International Journal of Emerging Trends in Engineering Research, Vol. 8, no 9, pp. 6240-6246, September 2020. https://doi.org/10.30534/ijeter/2020/21589202.
[18] N. Siddique. “Intelligent Control”, Springer International Publishing, Switzerland, 2014, pp.54-78. https://doi.org/10.1007/978-3-319-02135-5.
[19] P.V. de Campos Souza, “Fuzzy neural networks and neuro-fuzzy networks: A review the main techniques and applications used in the literature” Applied Soft Computing. Vol. 92, pp. 106275, July 2020. https://doi.org/10.1016/j.asoc.2020.106275.
[20] A.Tripathy, L.Panda, A.K Sahoo, S.K. Biswal, R.K Dwari, A.K. Sahu, “Statistical optimization study of jigging process on beneficiation of fine size high ash Indian non-coking coal”, Advanced Powder Technology, Vol. 27, no 4, pp. 1219-1224, 2016. https://doi.org/10.1016/j.apt.2016.04.006.
[21] A.K. Mukherjeea and B.K. Mishrab, “An integral assessment of the role of critical process parameters on jigging”, International Journal of Mineral Processing Vol. 81, no 3, pp. 187-200, December 2006. https://doi.org/10.1016/j.minpro.2006.08.005.
[22] N.(K.)M. Faber, “Estimating the uncertainty in estimates of root mean square error of prediction: application to determining the size of an adequate test set in multivariate calibration”, Chemometrics and Intelligent Laboratory Systems, Vol. 49, no 1, pp. 79-89, 6 September 1999, https://doi.org/10.1016/S0169-7439(99)00027-1.
Go to article

Authors and Affiliations

Yelena Kulakova
1
Waldemar Wójcik
2
Batyrbek Suleimenov
1
Andrzej Smolarz
2

  1. Satbaev University, Almaty, Kazakhstan
  2. Lublin University of Technology, Lublin, Poland
Download PDF Download RIS Download Bibtex

Abstract

The paper considers developed and offered an effective algorithm for solving the block-symmetrical tasks of polynomial computational complexity of data processing modular block-schemes designing. Currently, there are a large number of technologies and tools that allow you to create information systems of any class and purpose. To solve the problems of designing effective information systems, various models and methods are used, in particular, mathematical discrete programming methods. At the same time, it is known that such tasks have exponential computational complexity and can not always be used to solve practical problems. In this regard, there is a need to develop models and methods of the new class, which provide the solution of applied problems of discrete programming, aimed at solving problems of large dimensions. The work has developed and proposed block-symmetric models and methods as a new class of discrete programming problems that allow us to set and solve applied problems from various spheres of human activity. The issues of using the developed models are considered. and methods for computer-aided design of information systems (IS).

Go to article

Authors and Affiliations

Waldemar Wojcik
Aliya Kalizhanova
Sultan Akhmetov
Gulnaz Nabiyeva
Ainur Kozbakova
Download PDF Download RIS Download Bibtex

Abstract

The paper presents a solution to the problem of synthesis of control with respect to the sliding interval length for the optimization of a class of discrete linear multidimensional objects with a quadratic performance criterion. The equation of motion of a closed multidimensional discrete system in the general non-stationary case is derived based on the length of the optimization interval and their main properties. The closed-loop is fitted with a signal representing the predicted values averaged over the whole sliding interval of optimization with a certain weight. A problem with a sliding optimization interval may not require a real-time solution by means of a sequence of solutions on compressed intervals. Therefore, the study of control systems with optimization on a sliding interval is of undoubted interest for a number of practically important control problems.
Go to article

Authors and Affiliations

Zhazira Julayeva
1
Waldemar Wójcik
2
Gulzhan Kashaganova
3
Kulzhan Togzhanova
4
Saken Mambetov
4

  1. Academy of Logistics and Transport, Almaty Technological University, Almaty, Kazakhstan
  2. Lublin University of Technology, Lublin, Poland
  3. Turan University and Satbayev University, Almaty, Kazakhstan
  4. Almaty Technological University, Almaty, Kazakhstan
Download PDF Download RIS Download Bibtex

Abstract

Hereby there is given the speaker identification basic system. There is discussed application and usage of the voice interfaces, in particular, speaker voice identification upon robot and human being communication. There is given description of the information system for speaker automatic identification according to the voice to apply to robotic-verbal systems. There is carried out review of algorithms and computer-aided learning libraries and selected the most appropriate, according to the necessary criteria, ALGLIB. There is conducted the research of identification model operation performance assessment at different set of the fundamental voice tone. As the criterion of accuracy there has been used the percentage of improperly classified cases of a speaker identification.

Go to article

Authors and Affiliations

Yedilkhan Amirgaliyev
Timur Musabayev
Didar Yedilkhan
Waldemar Wójcik
Zhazira Amirgaliyeva
Download PDF Download RIS Download Bibtex

Abstract

The article considers information technology for the realization of human communication using residual human capabilities, obtained by organizing text entry using mobile and auxiliary devices. The components of the proposed technology are described in detail: the method for entering text information to realize the possibility of introducing a limited number of controls and the method of predicting words that are most often encountered after words already entered in the sentence. A generalized representation of the process of entering text is described with the aid of an ambiguous virtual keyboard and the representation of control signals for the selection of control elements. The approaches to finding the optimal distribution of the set of alphabet characters for different numbers of control signals are given. The method of word prediction is generalized and improved, the statistical language model with "back-off" is used, and the approach to the formation of the training corpus of the spoken Ukrainian language is proposed.

Go to article

Authors and Affiliations

Iurii V. Krak
Olexander V. Barmak
Ruslan O. Bahrii
Waldemar Wójcik
Saule Rakhmetullina
Saltanat Amirgaliyeva
Download PDF Download RIS Download Bibtex

Abstract

The article herein presents a new technique of controlling the system of collecting, storing and processing the information from the solar collectors, which might be applied to heating the industrial and domestic compartments for hot water supply. The most profitable usage of the solar collectors in the industry is replacement of a human interference with wireless sensor nets. The solar collector standard system consumes in average 30% of the heat due to poor control and configuration. Our monitoring and control system allows upgrade the performance of heating the industrial and domestic premises by means of solar collector for hot water supply.
Go to article

Authors and Affiliations

Waldemar Wojcik
1
Yedilhan Amirgaliyev
2
Murat Kunelbayev
2
Aliya Kalizhanova
2
Ainur Kozbakova
2
Talgat Sundetov
Didar Yedilkhan
3

  1. Lublin Technical University, Poland
  2. Institute of Information and Computational Technologies CS MES RK, Al-Farabi Kazakh National University
  3. Institute of Information and Computational Technologies CS MES RK, Astana IT University
Download PDF Download RIS Download Bibtex

Abstract

The article considers the problem of stability of interval-defined linear systems based on the Hurwitz and Lienard- Shipar interval criteria. Krylov, Leverier, and Leverier- Danilevsky algorithms are implemented for automated construction and analysis of the interval characteristic polynomial. The interval mathematics library was used while developing the software. The stability of the dynamic system described by linear ordinary differential equations is determined and based on the properties of the eigenvalues of the interval characteristic polynomial. On the basis of numerical calculations, the authors compare several methods of constructing the characteristic polynomial. The developed software that implements the introduced interval arithmetic operations can be used in the study of dynamic properties of automatic control systems, energy, economic and other non-linear systems.
Go to article

Bibliography

[1] Y. Y. Aleksankin, A. E. Brzhozovsky, V. A. Zhdanov and others, "Automateddesign of automatic control systems," ed. V. V. Solodovnikov, Moscow: Mashinostroenie, 1990, pp. 1-332.
[2] A. A. Voronov and I. A. Orourke, "Analysis and optimal synthesis of computer control systems," Moscow: Nauka, 1984, pp. 1–344.
[3] V. E. Balnokin and P. I. Chinaev, "Analysis and synthesis of automatic control systems on a computer. Algorithms and programs: Reference," Moscow: Radio and communications, 1991, pp 1–256.
[4] P. D. Krutko, A. I. Maximov and L. M. Skvortsov, "Algorithms and programs for designing automatic systems," Moscow: Radio and communications, 1988, 1–306.
[5] G. Davenport, I. Sira and E. Tournier, "Computer algebra," Moscow: Mir, 1991, pp. 1-352. [6] D. M. Klimov, V. M. Rudenko, "Methods of computer algebra in problems of mechanics," Moscow: Nauka, 1989, pp. 1–215.
[7] N. G. Chetayev, "Stability of motion," Moscow: GITL, 1955, pp. 1–207.
[8] V. I. Zubov, "Dynamics of managed systems," High School, 1982, pp. 1– 286.
[9] V. M. Matrosov, "On the theory of motion stability," Applied Mathematics and Mechanics, no 6, pp. 992-1002, 1962.
[10] R. Bellman, "Vector Lyapunov function," J. Soc. Indastr. Appl. Math., vol. 1., no 1, pp. 32-34, 1962.
[11] V. M. Matrosov and S. N. Vasilyev, "Comparison principle for derivation of theorems in mathematical system theory," International Conference on Artificial Intelligence. Moscow: USSR, 1975, pp. 25-34.
[12] V. M. Popov, "On the absolute stability of non-linear automatic control systems," Automatics and Telemechanics, vol. XXII, no. 8., pp. 50-59, 1961.
[13] V. M. Popov, "Hyper-Stability of automatic systems," Moscow: Nauka, 1970, pp. 1–456.
[14] V. Rezvan, "Absolute stability of automatic systems with delay," Moscow: Nauka, 1983, pp. 1–360.
[15] V. V. Rumyantsev and A. S. Oziraner "Stability and stabilization of motion in relation to a part of variables," Moscow: Nauka, 1987, pp. 1– 256.
[16] V. I. Vorotnikov, "Stability of dynamic systems in relation to some variables," Moscow: Nauka, 1991, pp. 1–288.
[17] K. G. Valeev and O. A. Zhautykov, "Infinite systems of differential equations," Alma-ATA: Nauka, 1974, pp. 1–415.
[18] A. K. Bedelbaev, "Stability of nonlinear automatic control systems," Almaty: ed. an KazSSR, 1960, pp. 1–163.
[19] B. J. Magarin, "The Stability and quality of non-linear automatic control systems," Almaty: Science of The Kazakh SSR, 1980. pp. 1–316.
[20] S. A. Aisagaliev, "Analysis and synthesis of autonomous nonlinear automatic control systems," Almaty: Science of The Kazakh SSR, 1980, pp. 1–244.
[21] R. E. Moor, "Interval analysis," New Jersey: Prentice-Hall, 1966, pp. 1- 245. [22] Y. I. Shokin, "Interval analyze," Novosibirsk: Science, 1986, pp. 1–224.
[23] T. I. Nazarenko and L. V. Marchenko, "Introduction to interval methods of computational mathematics, " Irkutsk: Publishing house of Irkutsk University, 1982, pp. 1–108.
[24] S. A. Kalmykov, Y. I. Shokin and Z. H. Yuldashev, "Methods of interval analyze. – Novosibirsk: Science, 1986. – 224 p.
[25] Yu. M. Gusev, V. N. Efanov, V. G. Krymsky and V. Yu. Rutkovsky, "Analysis and synthesis of linear interval dynamic systems (state of the problem)," RAN. Technical cybernetics, no. 1, 1991, pp. 3-30.
[26] E. M. Smagina, A. N. Moiseev and S. P. Moiseeva, "Methods for calculating the IHP coefficients of interval matrices," Computational Technologies, vol. 2, no.1. 1997, pp. 52-61.
[27] V. A. Pochukaev and I. M. Svetlov, "Analytical method of constructing Hurwitz interval polynomials," Automatics and Telemechanics, no. 2, 1996, pp. 89-100.
[28] N. A. Bobylev, S. V. Emelyanov and S. K. Korovin, "On positive definiteness of interval families of symmetric matrices," Automatics and Telemechanics, no. 8, 2000, pp. 5-10.
[29] S. B. Partushev, "Improving the accuracy of interval estimates of voltage deviations in General-purpose electrical networks," Computational Technology, no. 1, 1997, pp. 45-51.
[30] I. V. Svyd, A. I. Obod, G. E. Zavolodko, I. M. Melnychuk, W. Wójcik, S. Orazalieva and G. Ziyatbekova, "Assessment of information support quality by “friend or foe” identification systems," Przegląd Elektrotechniczny, vol. 95, no. 4, 2019, pp. 127-131.
[31] T. Zh. Mazakov, Sh. A. Jomartova, T. S. Shormanov, G. Z. Ziyatbekova, B. S. Amirkhanov and P. Kisala, "The image processing algorithms for biometric identification by fingerprints," News of the National Academy of Sciences of the Republic of Kazakhstan. Series of Geology and Technical Sciences, vol. 1, no 439. 2020, pp. 14-22.
[32] V. M. Belov, V. A. Sukhanov, E. V. Lagutina, "Interval approach for solving problems of kinetics of simple chemical reactions," Technol, no. 1, 1997, pp. 10-18.
[33] A. Kydyrbekova, M. Othman, O. Mamyrbayev, A. Akhmediyarova and Z. Bagashar, "Identification and authentication of user voice using DNN features and i-vector," Cogent Engineering, vol. 7, 2020, pp. 1-22.
[34] I. Nurdaulet, M. Talgat, M. Orken, G. Ziyatbekova, "Application of fuzzy and interval analysis to the study of the prediction and control model of the epidemiologic situation," Journal of Theoretical and Applied Information Technology, Pakistan, vol. 96, no. 14, 2018, pp. 4358-4368.
[35] V. N., Podlesny and V. G. Rubanov, "A simple frequency criterion for robust stability of a class of linear interval dynamic systems with delay," Automatics and Telemechanics, no. 9, 1996, pp. 131-139.
[36] A. P. Molchanov and M. V. Morozov, "Sufficient conditions for robust stability 5f linear non-stationary control systems with periodic interval restrictions," Automatics and Telemechanics, no. 1, 1997, pp. 100-107.
[37] A. M. Letov, "Stability of nonlinear control systems, " Moscow: Fizmatgiz, 1962, pp. 1–312.
[38] N. S. Bakhvalov, "Numerical methods," Moscow: Nauka, 1973. pp. 1–632.
[39] A. I. Lurie , "Some nonlinear problems of the automatic control theory," Moscow: GITL, 1951, pp. 1–216.
[40] K. I. Babenko, "Fundamentals of numerical analysis," Moscow: Nauka, 1986. pp. 1–744.
[41] B. P. Demidovich, I. A. Maron and E. Z. Shuvalova, "Numerical methods of analysis. Approximation of functions, differential and integral equations," Moscow: Nauka, 1967, pp. 1–368 p.
[42] V. N. Afanasiev, V. B. Kolmanovsky and V. R. Nosov, "Mathematical theory of designing control systems," Moscow: Higher. SHK., 1989, pp. 1–447.
[43] G.A. Amirkhanova, A. I. Golikov and Yu.G. Evtushenko, "On an inverse linear programming problem," Proceedings of the Steklov Institute of Mathematics, vol. 295. no. 1, 2016, pp. S21-S27.




Go to article

Authors and Affiliations

Talgat Mazakov
1
Waldemar Wójcik
2
Sholpan Jomartova
1
Nurgul Karymsakova
3
Gulzat Ziyatbekova
1
Aisulu Tursynbai
3

  1. Institute of Information and Computational Technologies CS MES RK, Al-Farabi Kazakh National University, Almaty, Kazakhstan
  2. Lublin Technical University, Poland
  3. Al-Farabi Kazakh National University, Almaty, Kazakhstan
Download PDF Download RIS Download Bibtex

Abstract

This paper represents a developed cryptographic information protection algorithm based on a substitutionpermutation network. We describe the cryptographic transformations used in the developed algorithm. One of the features of the algorithm is the simplicity of its modification with regard to different security levels. The algorithm uses a predeveloped S-box tested against differential and linear cryptanalysis. The S-box is consistent with one of the known standards AES and GOST R 34.12-2015. We provide the findings of an avalanche-effect investigation and statistical properties of ciphertexts. The algorithm actually meets the avalanche-effect criterion even after the first round.
Go to article

Authors and Affiliations

Rustem G. Biyashev
1
Nursulu A. Kapalova
1
Dilmuhanbet S. Dyusenbayev
1
Kunbolat T. Algazy
1
Waldemar Wojcik
2
Andrzej Smolarz
2

  1. Institute of Information and Computational Technologies of the Committee of Science of the Ministry of Education and Science of the Republic of Kazakhstan, Almaty
  2. Lublin University of Technology, Lublin, Poland
Download PDF Download RIS Download Bibtex

Abstract

The work considers a one-dimensional time series protocol packet intensity, measured on the city backbone network. The intensity of the series is uneven. Scattering diagrams are constructed. The Dickie Fuller test and Kwiatkowski-Phillips Perron-Shin-Schmitt test were applied to determine the initial series to the class of stationary or nonstationary series. Both tests confirmed the involvement of the original series in the class of differential stationary. Based on the Dickie Fuller test and Private autocorrelation function graphs, the Integrated Moving Average Autoregression Model model is created. The results of forecasting network traffic showed the adequacy of the selected model.
Go to article

Bibliography

[1] V. S. Maraev, “Time series visualization Tools in space research. Volume 1”, Research of science city, vol. 4, no. 22, 2017
[2] G.G. Kantorovich, “Analysis of temporal rows. Lecture and methodical materials”, Economic Journal of the Higher School of Economics, no. 3, 2002, pp. 379-701.
[3] M. S. Vershinina, “Analysis of assumptions about the stationarity of some temporal series”, Collection of the all-Russian conference on mathematics with international participation "IAC-2018", Barnaul: AltSU University, 2018, pp. 172-176.
[4] R. M. De Jong, C. Amsler, and P. Schmidt, “A robust version of the KPSS test, based on indicators”, J. Econometrics, vol. 137, no. 2, 2007, pp. 311–333.
[5] W. Wojcik, T. Bieganski, A, Kotyra, and A, Smolarz, "Application of forcasting algorithms in the optical fiber coal dust burner monitoring system", Proc. SPIE 3189, Technology and Applications of Light Guides, (5 August 1997); https://doi.org/10.1117/12.285618
[6] K. O. Kizbikenov, “Prognostication and temporary series: textbook by K. O. Kizbikenov”, Barnaul: AltSPU, 2017.
[7] V. S. Korolyuk, N. I. Portenko, A. V. Skorokhod, A. F. Turbin (eds.) “Handbook of probability theory and mathematical statistics”, Moscow: Nauka, 2005.
[8] G. Box, G. Jenkins, “Time Series Analysis: Forecasting and Control,” San Francisco: Holden-Day, 1970.
[9] I Rizkya, K Syahputri, R. M.Sari, I. Siregar and J. Utaminingrum, “Autoregressive Integrated Moving Average (ARIMA) Model of Forecast Demand in Distribution Centre,” Department of Industrial Engineering, Faculty of Engineering, Universitas Sumatera Utara in IOP Conf. Series: Materials Science and Engineering 598, 2019, 012071.
[10] N.Albanbay, B.Medetov, M. A. Zaks, “Statistics of Lifetimes for Transient Bursting States in Coupled Noisy Excitable Systems,” Journal of Computational and Nonlinear Dynamics. vol. 15, no. 12, 2020, https://doi.org/10.1115/1.4047867
Go to article

Authors and Affiliations

Tansaule Serikov
1
Аinur Zhetpisbayeva
1
Ainur Аkhmediyarova
2
Sharafat Mirzakulova
3
Aigerim Kismanova
1
Aray Tolegenova
1
Waldemar Wójcik
4

  1. S.Seifullin Kazakh AgroTechnical University, Nur-Sultan, Kazakhstan
  2. Institute of Information and Computational Technologies, Almaty, Kazakhstan
  3. Turan University, Almaty, Kazakhstan
  4. Lublin University of Technology, Poland

This page uses 'cookies'. Learn more