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All issues Volume 431 (2023) E3S Web Conf., 431 (2023) 05029 References
Open Access
Issue
E3S Web Conf.
Volume 431, 2023
XI International Scientific and Practical Conference Innovative Technologies in Environmental Science and Education (ITSE-2023)
Article Number 05029
Number of page(s) 8
Section IT and Mathematical Modeling in the Environment
DOI https://doi.org/10.1051/e3sconf/202343105029
Published online 13 October 2023
  1. I. I. Bosikov, N. V. Martyushev, R. V. Klyuev, I. A. Savchenko, V. V. Kukartsev., V. A. Kukartsev & Y. A. Tynchenko, Modeling and complex analysis of the topology parameters of ventilation networks when ensuring fire safety while developing coal and gas deposits. Fire, 6(3), 95 (2023) [CrossRef] [Google Scholar]
  2. I. S. Masich, V. S., Tyncheko, V. A. Nelyub, V. V. Bukhtoyarov, S. O. Kurashkin & A. S. Borodulin. Paired Patterns in Logical Analysis of Data for Decision Support in Recognition. Computation, 10(10), 185 (2022) [CrossRef] [Google Scholar]
  3. E. A. Kosenko and V. A. Nelyub, Evaluation of the stress–strain state of a polymer composition material with a hybrid matrix, Polymer Science, Series D, 15(2), 240-244 (2022) [CrossRef] [Google Scholar]
  4. V. Kukartsev et al. Analysis of Data in solving the problem of reducing the accident rate through the use of special means on public roads, 2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS) IEEE, 1-4 (2022) [Google Scholar]
  5. T. Kireev et al. Analysis of the Influence of Factors on Flight Delays in the United States Using the Construction of a Mathematical Model and Regression Analysis 2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), IEEE, 1-5 (2022) [Google Scholar]
  6. A. S. Mikhalev et al., The Orb-Weaving Spider Algorithm for Training of Recurrent Neural Networks. Symmetry, 14(10), 2036 (2022) [CrossRef] [Google Scholar]
  7. V. Kukartsev et al., Prototype Technology Decision Support System for the EBW Process, Proceedings of the Computational Methods in Systems and Software, Cham: Springer International Publishing, 456-466 (2022) [Google Scholar]
  8. I. S. Masich, V. S. Tynchenko, V. A. Nelyub, V. V. Bukhtoyarov, S. O. Kurashkin, A. P. Gantimurov & A. S. Borodulin. Prediction of Critical Filling of a Storage Area Network by Machine Learning Methods. Electronics, 11(24), 4150 (2022) [CrossRef] [Google Scholar]
  9. V. Kukartsev et al. Methods and Tools for Developing an Organization Development Strategy, 2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), IEEE, 1-8 (2022) [Google Scholar]
  10. V. A. Nelyub and I. A. Komarov, Technology of treatment of carbon fibers under electromagnetic influences of various origins to produce high-strength carbon fiber reinforced plastics, Russian Metallurgy, 1696-1699 (2021) [Google Scholar]
  11. B. V. Malozyomov, Improvement of Hybrid Electrode Material Synthesis for Energy Accumulators Based on Carbon Nanotubes and Porous Structures, Micromachines, 14(7), 1288 (2023) [CrossRef] [Google Scholar]
  12. V. O. Gutarevich et al., Reducing Oscillations in Suspension of Mine Monorail Track Applied Sciences, 13(8), 4671 (2023) [Google Scholar]
  13. B. V. Malozyomov et al., Overview of Methods for Enhanced Oil Recovery from Conventional and Unconventional Reservoirs, Energies, 16(13), 4907 (2023) [CrossRef] [Google Scholar]
  14. D. M. Strateichuk et al. Morphological Features of Polycrystalline CdS1− xSex Films Obtained by Screen-Printing Method, Crystals, 13(5), 825 (2023) [CrossRef] [Google Scholar]
  15. V. V. Bukhtoyarov et al., A Study on a Probabilistic Method for Designing Artificial Neural Networks for the Formation of Intelligent Technology Assemblies with High Variability, Electronics, 12(1), 215 (2023) [CrossRef] [Google Scholar]
  16. W. M. van der process management: a personal view. Business Process Management Journal, 10(2) (2004) [Google Scholar]
  17. M. Kirchmer & A.W. Scheer, Business process automation—combining best and next practices. Business Process Automation: ARIS in Practice, 1-15 (2004) [Google Scholar]
  18. K. Moiseeva et al. The Impact of Coal Generation on the Ecology of City Areas, 2023 22nd International Symposium INFOTEH-JAHORINA (INFOTEH), IEEE, 1-6 (2023) [Google Scholar]
  19. I. A. Barantsov et al. Classification of Acoustic Influences Registered with Phase-Sensitive OTDR Using Pattern Recognition Methods, Sensors, 23(2), 582 (2023) [CrossRef] [Google Scholar]
  20. V. A. Nelyub, et al., Properties of Carbon Fibers after Applying Metal Coatings on Them by Magnetron Sputtering Technology, Fibre Chemistry, 53(4), 252-257 (2021) [CrossRef] [Google Scholar]
  21. V. A. Lomazov, D. A. Petrosov, D. Yu. Evsyukov, Intellectual assessment of staff sufficiency for innovative development of the sustainable regional agro-industrial complex, IOP Conference Series: Earth and Environmental Science, 981(2) (2022) [Google Scholar]
  22. B. V. Malozyomov et al., Study of Supercapacitors Built in the Start-Up System of the Main Diesel Locomotive, Energies, 16(9), 3909 (2023) [CrossRef] [Google Scholar]
  23. B. V. Malozyomov et al., Substantiation of Drilling Parameters for Undermined Drainage Boreholes for Increasing Methane Production from Unconventional Coal-Gas Collectors, Energies, 16(11), 4276 (2023) [CrossRef] [Google Scholar]
  24. A. Rassokhin, A. Ponomarev, A. Karlina, Nanostructured high-performance concretes based on low-strength aggregates, Magazine of Civil Engineering, 110(2), 11015 (2022) [Google Scholar]
  25. A. Shutaleva et al., Migration potential of students and development of human capital, Education Sciences, 12(5), 324 (2022) [CrossRef] [Google Scholar]
  26. A. Shutaleva et al. Environmental behavior of youth and sustainable development, Sustainability, 14(1), 250 (2021) [CrossRef] [Google Scholar]
  27. A. E. Balanovskiy et al., Determination of rail steel structural elements via the method of atomic force microscopy, CIS Iron Steel Rev, 23, 86-91 (2022) [CrossRef] [Google Scholar]
  28. V. V. Kondrat’ev et al., Description of the complex of technical means of an automated control system for the technological process of thermal vortex enrichment, J. of Physics: Conference Series, IOP Publishing, 1661(1), 12101 (2022) [Google Scholar]
  29. Scheer, August-Wilhelm, et al. Business process automation. ARIS in practice (2004) [Google Scholar]
  30. A. Santiago and A. Rodriguez, Automation of a business process using robotic process automation (RPA): A case study. Applied Computer Sciences in Engineering: 4th Workshop on Engineering Applications, 27-29 (2017) [Google Scholar]
  31. E. F. Watson, H. Karyn, Business process automation. Springer Handbook of Automation, 1597-1612 (2009) [Google Scholar]
  32. Y. Rizk, et al., A unified conversational assistant framework for business process automation." arXiv preprint arXiv, 2001, 03543 (2020) [Google Scholar]
  33. L. Ivancic, V. Dalia Susa, B. V. Vesna, Robotic process automation: systematic literature review. Business Process Management: Blockchain and Central and Eastern Europe Forum: BPM 2019 Blockchain and CEE Forum, 1–6 (2019) [Google Scholar]
  34. G. Shidaganti, et al., Robotic process automation with AI and OCR to improve business process. Second International Conference on Electronics and Sustainable Communication Systems (ICESC). IEEE, (2021) [Google Scholar]
  35. R. Torkhani, et al., Intelligent framework for business process automation and re-engineering. International Conference on Intelligent Systems (IS). IEEE, (2018) [Google Scholar]

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