10 январ 2026
2FLOTATSIYA MASHINASINING SIRT KO‘PIKLI QATLAMIDAGI PUFAKCHALAR TEZLIGINI HISOBLASH USULLARI
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[11] Betancourt, F., Bürger, R., Diehl, S., Gutiérrez, L., Martí, M. C., & Vásquez, Y. A. (2023). A model of froth flotation with drainage: Simulations and comparison with experiments. Minerals, 13(3), Article 344. https://doi.org/10.3390/min13030344
[1] Nguyen, T. P., Tran, T. H., Nguyen, T. A. H., Nguyen, N. N., & Nguyen, A. V. (2025). The role of surface mobility in enhancing froth drainage and reducing entrainment in flotation. Minerals Engineering, 233, Article 109632. https://doi.org/10.1016/j.mineng.2025.109632
[2] Aldrich, C., & Liu, X. (2021). Monitoring of flotation systems by use of multivariate froth image analysis. Minerals, 11(7), Article 683. https://doi.org/10.3390/min11070683
[3] Ammar, A., Fredj, H. B., & Souani, C. (2021). Accurate realtime motion estimation using optical flow on an embedded system. Electronics, 10(17), Article 2164. https://doi.org/10.3390/electronics10172164
[4] Kosior, D., Wiertel-Pochopien, A., Kowalczuk, P. B., & Zawala, J. (2023). Bubble formation and motion in liquids—A review. Minerals, 13(9), Article 1130. https://doi.org/10.3390/min13091130
[5] Shahbazi, B. (2015). Study of relationship between flotation rate and bubble surface area flux using bubble-particle attachment efficiency. American Journal of Chemical Engineering, 3(2-2), 6–12. https://doi.org/10.11648/j.ajche.s.2015030202.12
[6] Alfarano, A., Maiano, L., Papa, L., & Amerini, I. (2024). Estimating optical flow: A comprehensive review of the state of the art. Computer Vision and Image Understanding, 249, Article 104160. https://doi.org/10.1016/j.cviu.2024.104160
[7] Wang, J., Forbes, G., & Forbes, E. (2022). Frother characterization using a novel bubble size measurement technique. Applied Sciences, 12(2), Article 750. https://doi.org/10.3390/app12020750
[8] Fleet, D. J., & Weiss, Y. (2006). Optical flow estimation. In N. Paragios, Y. Chen, & O. Faugeras (Eds.), Handbook of mathematical models in computer vision (pp. 237–257). Springer. https://doi.org/10.1007/0-387-28831-7_15
[9] Huang, T. (2018). Traffic speed estimation from surveillance video data. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (pp. 161–1614).
[10] Jávor, Z., Schreithofer, N., & Heiskanen, K. (2018). Kernel functions to flotation bubble size distributions. Minerals Engineering, 125, 200–205. https://doi.org/10.1016/j.mineng.2018.06.006
[12] Sangsuwan, K., & Ekpanyapong, M. (2024). Video-based vehicle speed estimation using speed measurement metrics. IEEE Access, 12, 4845–4858. https://doi.org/10.1109/ACCESS.2024.3356789
[1] Nguyen, T. P., Tran, T. H., Nguyen, T. A. H., Nguyen, N. N., & Nguyen, A. V. (2025). The role of surface mobility in enhancing froth drainage and reducing entrainment in flotation. Minerals Engineering, 233, Article 109632. https://doi.org/10.1016/j.mineng.2025.109632
[2] Aldrich, C., & Liu, X. (2021). Monitoring of flotation systems by use of multivariate froth image analysis. Minerals, 11(7), Article 683. https://doi.org/10.3390/min11070683
[3] Ammar, A., Fredj, H. B., & Souani, C. (2021). Accurate realtime motion estimation using optical flow on an embedded system. Electronics, 10(17), Article 2164. https://doi.org/10.3390/electronics10172164
[4] Kosior, D., Wiertel-Pochopien, A., Kowalczuk, P. B., & Zawala, J. (2023). Bubble formation and motion in liquids—A review. Minerals, 13(9), Article 1130. https://doi.org/10.3390/min13091130
[5] Shahbazi, B. (2015). Study of relationship between flotation rate and bubble surface area flux using bubble-particle attachment efficiency. American Journal of Chemical Engineering, 3(2-2), 6–12. https://doi.org/10.11648/j.ajche.s.2015030202.12
[6] Alfarano, A., Maiano, L., Papa, L., & Amerini, I. (2024). Estimating optical flow: A comprehensive review of the state of the art. Computer Vision and Image Understanding, 249, Article 104160. https://doi.org/10.1016/j.cviu.2024.104160
[7] Wang, J., Forbes, G., & Forbes, E. (2022). Frother characterization using a novel bubble size measurement technique. Applied Sciences, 12(2), Article 750. https://doi.org/10.3390/app12020750
[8] Fleet, D. J., & Weiss, Y. (2006). Optical flow estimation. In N. Paragios, Y. Chen, & O. Faugeras (Eds.), Handbook of mathematical models in computer vision (pp. 237–257). Springer. https://doi.org/10.1007/0-387-28831-7_15
[9] Huang, T. (2018). Traffic speed estimation from surveillance video data. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (pp. 161–1614).
[10] Jávor, Z., Schreithofer, N., & Heiskanen, K. (2018). Kernel functions to flotation bubble size distributions. Minerals Engineering, 125, 200–205. https://doi.org/10.1016/j.mineng.2018.06.006
[11] Betancourt, F., Bürger, R., Diehl, S., Gutiérrez, L., Martí, M. C., & Vásquez, Y. A. (2023). A model of froth flotation with drainage: Simulations and comparison with experiments. Minerals, 13(3), Article 344. https://doi.org/10.3390/min13030344
[12] Sangsuwan, K., & Ekpanyapong, M. (2024). Video-based vehicle speed estimation using speed measurement metrics. IEEE Access, 12, 4845–4858. https://doi.org/10.1109/ACCESS.2024.3356789