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All issues Volume 567 (2024) E3S Web Conf., 567 (2024) 01018 References
Open Access
Issue
E3S Web Conf.
Volume 567, 2024
8th International Conference “Physical & Chemical Geotechnologies” 2024
Article Number 01018
Number of page(s) 15
DOI https://doi.org/10.1051/e3sconf/202456701018
Published online 09 September 2024
  1. Tsopa, V., Cheberiachko, S., Yavorska, O., Deryugin, O., & Bas, I. (2022). Increasing the safety of the transport process by minimizing the professional risk of a dump truck driver. Mining of Mineral Deposits, 16(3), 101–108. https://doi.org/10.33271/mining16.03.101 [CrossRef] [Google Scholar]
  2. Peng, S., Cheng, X., Yu, M., Feng, X., Geng, X., Zhao, S., & Wang, P. (2023). Collision risk assessment and operation assistant strategy for teleoperation system. Applied Sciences, 3(7), 4109. https://doi.org/10.3390/app13074109 [CrossRef] [Google Scholar]
  3. Mamaikin, O., Sotskov, V., Demchenko, Y., & Prykhorchuk, O. (2018). Productive flows control in coal mines under the condition of diversification of production. E3S Web of Conferences, (60), 00008. https://doi.org/10.1051/e3sconf/20186000008 [CrossRef] [EDP Sciences] [Google Scholar]
  4. Fomychov, V., Mamaikin, O., Demchenko, Y., Prykhorchuk, O., & Jarosz, J. (2018). Analysis of the efficiency of geomechanical model of mine working based on computational and field studies. Mining of Mineral Deposits, 12(4), 46–55. https://doi.org/10.15407/mining12.04.046 [CrossRef] [Google Scholar]
  5. Pan, M., Li, J., Yang, X., Wang, S., Pan, L., Su, T., Wang, Y., Yang, Q., & Liang, K. (2022). Collision risk assessment and automatic obstacle avoidance strategy for teleoperation robots. Computers & Industrial Engineering, (169), 108275. https://doi.org/10.1016/j.cie.2022.108275 [CrossRef] [Google Scholar]
  6. Khorolskyi, A., Hrinov, V., Mamaikin, O., & Demchenko, Y. (2019). Models and methods to make decisions while mining production scheduling. Mining of Mineral Deposits, 13(4), 53–62. https://doi.org/10.33271/mining13.04.053 [CrossRef] [Google Scholar]
  7. Kononenko, M., Khomenko, O., Cabana, E., Prostański, D., & Dychkovskyi, R. (2023). Using the methods to calculate parameters of drilling and +blasting operations for emulsion explosives. Acta Montanistica Slovaca, 28(v28/i3), 655–667. https://doi.org/10.46544/ams.v28i3.10 [CrossRef] [Google Scholar]
  8. Polyanska, A., Pazynich, Y., Mykhailyshyn, K., Babets, D. & Toś, P. (2024). Aspects of energy efficiency management for rational energy resource utilization. Rudarsko-Geološko-Naftni Zbornik, 39(3), 13–26. https://doi.org/10.17794/rgn.2024.3.2 [CrossRef] [Google Scholar]
  9. Lewinska, P., Matula, R., & Dyczko, A. (2017). Integration of thermal digital 3D model and a MASW (Multichannel Analysis of Surface Wave) as a means of improving monitoring of spoil tip stability. 2017 Baltic Geodetic Congress (BGC Geomatics). https://doi.org/10.1109/bgc.geomatics.2017.29 [Google Scholar]
  10. Kononenko, M., Khomenko, O., Kosenko, A., Myronova, I., Bash, V., & Pazynich, Y. (2024). Raises advance using emulsion explosives. E3S Web of Conferences, (526), 01010. https://doi.org/10.1051/e3sconf/202452601010 [CrossRef] [EDP Sciences] [Google Scholar]
  11. Dychkovskiy, R., & Bondarenko, V. (2006). Methods of extraction of thin and rather thin coal seams in the works of the scientists of the Underground Mining Faculty (National Mining University). International Mining Forum 2006, New Technological Solutions in Underground Mining, 21–25. https://doi.org/10.1201/noe0415401173.ch3 [CrossRef] [Google Scholar]
  12. Dyczko, A. (2007). Thin coal seams, their role in the reserve base of Poland. Technical, Technological and Economical Aspects of Thin-Seams Coal Mining, International Mining Forum, 2007, 81–87. https://doi.org/10.1201/noe0415436700.ch10 [CrossRef] [Google Scholar]
  13. Sobolev, V., Bilan, N., Dychkovskyi, R., Caseres Cabana, E., & Smolinski, A. (2020). Reasons for breaking of chemical bonds of gas molecules during movement of explosion products in cracks formed in rock mass. International Journal of Mining Science and Technology, 30(2), 265–269. https://doi.org/10.1016/j.ijmst.2020.01.002 [CrossRef] [Google Scholar]
  14. Gopinath, V., Johansen, K., & Ölvander, J. (2018). Risk assessment for collaborative operation: A case study on hand-guided industrial robots. In Risk Assessment (pp. 167–187). https://doi.org/10.5772/intechopen.70607 [Google Scholar]
  15. Bettini, A., Marayong, P., Lang, S., Okamura, A.M., & Hager, G.D. (2004). Vision-assisted control for manipulation using virtual fixtures. Transactions on Robotics, 20(6), 953–966. https://10.1109/TRO.2004.829483 [CrossRef] [Google Scholar]
  16. Buktukov, N.S., Gumennikov, Y.S., Moldabayeva, G.Z., Buktukov, B.Z., & Yesbergenova, E.S. (2024). New solutions for mechanized small diameter shaft sinking for residual oil production. SOCAR Proceedings, (1), 81–86. https://doi.org/10.5510/OGP20240100944 [CrossRef] [Google Scholar]
  17. Abi-Farraj, F., Pacchierotti, C., Arenz, O., Neumann, G., & Giordano, P.R. (2020). A haptic shared-control architecture for guided multi-target robotic grasping. IEEE Transactions on Haptics, (13), 270–285. https://doi.org/10.1109/TOH.2019.2913643 [CrossRef] [PubMed] [Google Scholar]
  18. Tanaka, T., Takubo, T., Inoue, K., & Arai, T. (2006). Emergent stop for Humanoid Robots. 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 3970–3975 https://doi.org/10.1109/iros.2006.281833 [Google Scholar]
  19. Ni, D., Yew, A.W.W., Ong, S.K., & Nee, A.Y.C. (2017). Haptic and visual augmented reality interface for programming welding robots. Advances in Manufacturing, (5), 191–198. https://doi.org/10.1007/s40436-017-0184-7 [CrossRef] [Google Scholar]
  20. Zanchettin, AM, Ceriani, NM, Rocco, P., Ding, H., & Matthias, B. (2016). Safety in human-robot collaborative manufacturing environments: Metrics and control. IEEE Transactions on Automation Science and Engineering, 13(2), 882–893. https://doi.org/10.1109/TASE.2015.2412256 [CrossRef] [Google Scholar]
  21. Bazaluk, O., Ashcheulova, O., Mamaikin, O., Khorolskyi, A., Lozynskyi, V., & Saik, P. (2022). Innovative activities in the sphere of mining process management. Frontiers in Environmental Science, (10), 878977. https://doi.org/10.3389/fenvs.2022.878977 [CrossRef] [Google Scholar]
  22. Yelemessov, K., Nauryzbayeva, D., Bortebayev, S., Baskanbayeva, D., & Chubenko, V. (2021). Efficiency of application of fiber concrete as a material for manufacturing bodies of centrifugal pumps. E3S Web of Conferences, (280), 07007. https://doi.org/10.1051/e3sconf/202128007007 [CrossRef] [EDP Sciences] [Google Scholar]
  23. Vatalis, K.I., Avlogiaris, G., & Tsalis, T.Α. (2022). Just transition pathways of energy decarbonization under the global environmental changes. Journal of Environmental Management, (309), 114713. https://doi.org/10.1016/j.jenvman.2022.114713 [CrossRef] [PubMed] [Google Scholar]
  24. Wang, T.-M., Tao, Y., & Liu, H. (2018). Current researches and future development trends of intelligent robots: A Review. International Journal of Automation and Computing, 15(5), 525–546. https://doi.org/10.1007/s11633-018-1115-1 [CrossRef] [Google Scholar]
  25. Lane, S.N. (2017). Natural flood management. WIREs Water, 4(3), e1211. https://doi.org/10.1002/wat2.1211 [CrossRef] [Google Scholar]
  26. Blagojević, B., Vasilevska, L., Anđelković, D., Bogojević, A., & Lousada, S. (2023). A framework for assessing nature-based urban stormwater management solutions: A preliminary spatial analysis approach applied to Southeast Serbia. Water, 15(20), 3604. https://doi.org/10.3390/w15203604 [CrossRef] [Google Scholar]
  27. Reinhart, R., Dang, T., Hand, E., Papachristos, C., & Alexis, K. (2020). Learning-based path planning for autonomous exploration of subterranean environments. IEEE International Conference on Robotics and Automation (ICRA), 1215–1221. https://doi.org/10.1109/ICRA40945.2020.9196662 [Google Scholar]
  28. Sala, D., Pavlov, K., Pavlova, O., Dychkovskyi R., Ruskykh, V., & Pysanko, S. (2023). Determining the level of efficiency of gas distribution enterprises in the Western Region of Ukraine. Inżynieria Mineralna, 2(2(52)), 109–122. https://doi.org/10.29227/im-2023-02-64 [Google Scholar]
  29. Miseikis, J., Caroni, P., Duchamp, P., Gasser, A., Marko, R., Miseikiene, N., Zwilling, F., de Castelbajac, C., Eicher, L., Fruh, M., & Fruh, H. (2020). Lio-A personal robot assistant for human-robot interaction and care applications. IEEE Robotics and Automation Letters, 5(4), 5339–5346. https://doi.org/10.1109/lra.2020.3007462 [CrossRef] [PubMed] [Google Scholar]
  30. Yesmakhanova, L.N., Tulenbayev, M.S., Chernyavskaya, N.P., Beglerova, S.T., Kabanbayev, A.B., Abildayev, A.A., & Maussymbayeva, A.D. (2021). Simulating the coal dust combustion process with the use of the real process parameters. ARPN Journal of Engineering and Applied Sciences, 16(22), 2395–2407. [Google Scholar]
  31. Yelemessov, K., Krupnik, L., Bortebayev, S., Beisenov, B., Baskanbayeva, D., & Igbayeva, A. (2020). Polymer concrete and fibre concrete as efficient materials for manufacture of gear cases and pumps. E3S Web of Conferences, (168), 00018. https://doi.org/10.1051/e3sconf/20201680001 [CrossRef] [EDP Sciences] [Google Scholar]
  32. Krupnik, L., Yelemessov, K., Beisenov, B., & Baskanbayeva, D. (2020). Substantiation and process design to manufacture polymer-concrete transfer cases for mining machines. Mining of Mineral Deposits, 14(2), 103–109. https://doi.org/10.33271/mining14.02.10 [CrossRef] [Google Scholar]
  33. Yang, G., Pang, Z., Deen, MJ, Dong, M., Zhang, YT, Lovell, N., & Rahmani, AM (2020). Homecare robotic systems for healthcare 4.0: visions and enabling technologies. IEEE Journal of Biomedical and Health Informatics, 24(9), 2535–2549. https://doi.org/10.1109/JBHI.2020.2990529 [CrossRef] [PubMed] [Google Scholar]
  34. Kemajl, Z., Stojance, M., Gzim, I., & Ledi, M.L. (2024). Comprehensive analysis of the mining accident forecasting and risk assessment methodologies: Case study – Stanterg Mine. Mining of Mineral Deposits, 18(2), 11–17. https://doi.org/10.33271/mining18.02.011 [CrossRef] [Google Scholar]
  35. Dyczko, A., Galica, D., & Sypniowski, S. (2012). Deposit model as a first step in mining production scheduling. Geomechanical Processes During Underground Mining – Proceedings of the School of Underground Mining, 231–247. https://doi.org/10.1201/b13157-38 [Google Scholar]
  36. Dychkovskyi, R., Falshtynskyi, V., Ruskykh, V., Cabana, E., & Kosobokov, O. (2018). A modern vision of simulation modelling in mining and near mining activity. E3S Web of Conferences, (60), 00014. https://doi.org/10.1051/e3sconf/20186000014 [CrossRef] [EDP Sciences] [Google Scholar]
  37. Pivnyak, G., Dychkovskyi, R., Smirnov, A., & Cherednichenko, Y. (2013). Some aspects on the software simulation implementation in thin coal seams mining. Energy Efficiency Improvement of Geotechnical Systems, 1–10. https://doi.org/10.1201/b16355-2 [Google Scholar]
  38. Kicki, J., & Dyczko, A. (2010). The concept of automation and monitoring of the production process in an underground mine. New Techniques and Technologies in Mining – Proceedings of the School of Underground Mining, 245–253. https://doi.org/10.1201/b11329-41 [Google Scholar]
  39. Falshtynskyi, V., Dychkovskyi, R., Khomenko, O., & Kononenko, M. (2020). On the formation of a mine-based energy resource complex. E3S Web of Conferences, (201), 01020. https://doi.org/10.1051/e3sconf/202020101020 [CrossRef] [EDP Sciences] [Google Scholar]
  40. Murashov, V., Hearl, F., & Howard, J. (2016). Working safely with robot workers: Recommendations for the new workplace. Journal of Occupational and Environmental Hygiene, 13(3), D61–71. https://doi.org/10.1080/15459624.2015.1116700 [CrossRef] [PubMed] [Google Scholar]
  41. Golinko, V., Cheberyachko, S., Deryugin, O., Tretyak, O., & Dusmatova, O. (2020). Assessment of the risks of occupational diseases of the passenger bus drivers. Safety and Health at Work, 11(4), 543–549. https://doi.org/10.1016/j.shaw.2020.07.005 [CrossRef] [PubMed] [Google Scholar]
  42. Rosca, S.-D., & Leba, M. (2017). Using brain-computer-interface for robot arm control. MATEC Web of Conferences, (121), 08006. https://doi.org/10.1051/matecconf/201712108006 [CrossRef] [EDP Sciences] [Google Scholar]
  43. Bazaluk, O., Tsopa, V., Cheberiachko, S., Deryugin, O., Radchuk, D., Borovytskyi, O., & Lozynskyi, V. (2023). Ergonomic risk management process for safety and health at work, Frontiers in Public Health, (11), 1253141. https://doi.org/10.3389/fpubh.2023.1253141 [CrossRef] [PubMed] [Google Scholar]
  44. Bazaluk, O., Tsopa, V., Okrasa, M., Pavlychenko, A., Cheberiachko, S., Yavorska, O., Deryugin, O., & Lozynskyi, V. (2023). Improvement of the occupational risk management process in the work safety system of the enterprise. Frontiers in Public Health, (11). https://doi.org/10.3389/fpubh.2023.1330430 [PubMed] [Google Scholar]
  45. Tsopa, V.A., Cheberiachko, S.I., Yavorska, O.O., Deryugin, O.V., & Aleksieiev, A.A. (2022). Improvement of the safe work system. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (6), 104–111. https://doi.org/10.33271/nvngu/2022-6/104 [CrossRef] [Google Scholar]
  46. Bazaluk, O., Koriashkina, L., Cheberiachko, S., Deryugin, O., Odnovol, M., Lozynskyi, V., & Nesterova, O. (2022). Methodology for assessing the risk of incidents during passenger road transportation using the functional resonance analysis method. Heliyon, (8), e11814 https://doi.org/10.1016/j.heliyon.2022.e11814 [CrossRef] [PubMed] [Google Scholar]
  47. Sotelo Asef, J.G. (2018). ISO 19001:2011 standard planning of the audit in a system of quality management on the basis of standard ISO 19011:2011. RIDE Revista Iberoamericana Para La Investigación y El Desarrollo Educativo, 8(16), 97–129. https://doi.org/10.23913/ride.v8i16.329 [CrossRef] [Google Scholar]
  48. Rathmair, M., & Brandstötter, M. (2021). Safety as Bad Cop of physical assistance systems? In Smart Technologies for Precision Assembly, 344–357. https://doi.org/10.1007/978-3-030-72632-4_26 [Google Scholar]
  49. Ross, E., Day, M., Ivanova, C., McLeod, A., & Lockshin, J. (2022). Intersections of disadvantaged communities and renewable energy potential: Data set and analysis to inform equitable investment prioritization in the United States. Renewable Energy Focus, (41), 1–14. https://doi.org/10.1016/j.ref.2022.02.002 [CrossRef] [Google Scholar]
  50. Standard DSTU EN ISO 12100:2016. (2016). Safety of machines. General design principles. Risk assessment and risk reduction (EN ISO 12100:2010, IDT; ISO 12100:2010, IDT). Retrieved from https://online.budstandart.com/ua/catalog/doc-page?id_doc=71627 [Google Scholar]
  51. Daniş, F.S., Naskali, A.T., Cemgil, A.T., & Ersoy, C. (2022). An indoor localization dataset and data collection framework with high precision position annotation. Pervasive and Mobile Computing, (81), 101554. http://dx.doi.org/10.1016/j.pmcj.2022.101554 [Google Scholar]
  52. Lanza, F., Seidita, V., & Chella, A. (2020). Agents and robots for collaborating and supporting physicians in healthcare scenarios. Journal of Biomedical Informatics, (108), 103483. https://doi.org/10.1016/j.jbi.2020.103483 [CrossRef] [PubMed] [Google Scholar]
  53. Dino, M.J.S., Davidson, P.M., Dion, K.W., Szanton, S.L., & Ong, I.L. (2022). Nursing and human-computer interaction in healthcare robots for older people: An integrative review. International Journal of Nursing Studies Advances, (4), 100072. https://doi.org/10.1016/j.ijnsa.2022.100072 [Google Scholar]
  54. Nyameke, E. (2013). Feasibility study of implementing an industrial robot for induction hardening machine. Retrieved from https://urn.fi/URN:NBN:fi:amk-2013102216255 [Google Scholar]
  55. Weidemann, C., Mandischer, N., van Kerkom, F., Corves, B., Hüsing, M., Kraus, T., & Garus, C. (2023). Literature review on recent trends and perspectives of collaborative robotics in Work 4.0. Robotics, (12), 84. https://doi.org/10.3390/robotics12030084 [CrossRef] [Google Scholar]
  56. Pauliková, A., Gyurák Babeľová, Z., & Ubárová, M. (2021). Analysis of the impact of humancobot collaborative manufacturing implementation on the occupational health and safety and the quality requirements. International Journal of Environmental Research and Public Health, 18(4), 1927. https://doi.org/10.3390/ijerph18041927 [CrossRef] [PubMed] [Google Scholar]
  57. Simões, AC, Pinto, A., Santos, J., Pinheiro, S., & Romero, D. (2022). Designing human-robot collaboration (HRC) workspaces in industrial settings: A systematic literature review. Journal of Manufacturing Systems, (62), 28–43. https://doi.org/10.1016/j.jmsy.2021.11.007 [CrossRef] [Google Scholar]
  58. Shi, W., Jiang, X., Hu, J. Abdelgader, AMS, Teng, Y., Wang, Y., He, H., Dong, R., Shu, F., & Wang, J. (2022). Physical layer security techniques for data transmission for future wireless networks. Security and Safety, (1), 2022007. https://doi.org/10.1051/sands/2022007 [CrossRef] [EDP Sciences] [Google Scholar]
  59. Bazaluk, O., Pavlychenko, A., Yavorska, O., Nesterova, O., Cheberiachko, S., Deryugin, O., & Lozynskyi, V. (2024). Improving the risk management process in quality management systems of higher education. Scientific Reports, (14), 3977. https://doi.org/10.1038/s41598-024-53455-9 [CrossRef] [PubMed] [Google Scholar]
  60. Bhatt, P.M., Malhan, R.K., Shembekar, A.V., Yoon, Y.J., & Gupta, S.K. (2020). Expanding capabilities of additive manufacturing through the use of robotics technologies: A survey. Additive manufacturing, (31), 100933. https://doi.org/10.1016/j.addma.2019.100933 [CrossRef] [Google Scholar]
  61. Cheberiachko, S., Yavorska, O., Deryugin, O., Lantukh, D., Bas, I., Kruzhilko, O., & Melnyk, V. (2023). Improving safety of passenger road transportation. Transactions on transport sciences, 14(2), 11–20. https://doi.org/10.5507/tots.2023.003 [CrossRef] [Google Scholar]
  62. Yaacoub, J.-P.A., Noura, H.N., Salman, O., & Chehab, A. (2021). Robotics cyber security: vulnerabilities, attacks, countermeasures, and recommendations. International Journal of Information Security, 21(1), 115–158. https://doi.org/10.1007/s10207-021-00545-8 [Google Scholar]
  63. Gong, C., Yue, X., Zhang, Z., Wang, X., & Dai, X. (2021). Enhancing Physical Layer Security With Artificial Noise in Large-Scale NOMA Networks. IEEE Transactions on Vehicular Technology, (70), 2349–2361. https://doi.org/10.1109/TVT.2021.3057661 [CrossRef] [Google Scholar]
  64. Hamamreh, J.M., Furqan, H.M., & Arslan, H. (2018) Classifications and Applications of Physical Layer Security Techniques for Confidentiality: A Comprehensive survey. IEEE Communications Surveys & Tutorials, (21), 1773–1828. https://doi.org/10.1109/COMST.2018.2878035 [Google Scholar]
  65. Yuliana, M., & Wirawan, S. (2019). A simple secret key generation by using a combination of pre-processing method with a multilevel quantization. Entropy, (21), 192. https://doi.org/10.3390/e21020192 [CrossRef] [PubMed] [Google Scholar]
  66. Tsopa, V., Cheberiachko, S., Cheberiachko, Y., Deryugin, O., Chencheva, O., Rieznik, D., Klimov, E., Lashko, Y., Pashko, D., & Biliaieva, V. (2024). Development of a new ergonomic risks management algorithm on the example of drivers. Eastern-European Journal of Enterprise Technologies, 2(3(128), 38–49. https://doi.org/10.15587/1729-4061.2024.302886 [CrossRef] [Google Scholar]
  67. Phillipson, F., Neumann, N., & Wezeman, R. (2023). Classification of hybrid quantum-classical computing. Computational Science – ICCS 2023, 18–33. https://doi.org/10.1007/978-3-031-36030-5_2 [CrossRef] [Google Scholar]
  68. Ding, Y., & Fusco, V. (2015). Orthogonal vector approach for synthesis of multi-beam directional modulation transmitters. IEEE Antennas and Wireless Propagation Letters, (14), 1330–1333. https://doi.org/10.1109/LAWP.2015.2404818 [CrossRef] [Google Scholar]

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