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1. Post-quantum multi-factor authentication in multi-domain identity federations with adaptive security policy management: (Content №4 2026); ... confirmed a 30–40 % reduction in session compromise probability and a 15 % increase in risk prediction accuracy while maintaining acceptable latency thresholds. The proposed solution integrates seamlessly ...; Created on 24 August 2026
2. A hybrid ANN–FEM framework for high accuracy slope stability prediction: (Content №4 2026); ... Abstract: Purpose. To develop a hybrid methodology that integrates Artificial Neural Networks (ANN) with Finite Element Method (FEM) simulations for the rapid and accurate prediction of slope stability. ...; Created on 24 August 2026
3. Comparison of impulse processes in spatially shifted ring-like cores made of ferrite and thin sheet steel: (Content №4 2026); ... 11. Ibrahim, M., & Pillay, P. (2012). Core loss prediction in electrical machine laminations considering skin effect and minor hysteresis loops. 2012 IEEE Energy Conversion Congress and Exposition ...; Created on 24 August 2026
4. Stability and bifurcations of eccentrically reinforced compound shell structures by means of computer algebra: (Content №4 2026); ... Z., & Sirenko, V. M. (Eds.) (2020). Mathematical Models and Prediction of Damage Loads in Rocket-Space Systems: collective monograph. Zaporizhzhia: Vydavnychyi dim “Helvetyka”. ISBN 978-966-992-583-1. ...; Created on 24 August 2026
5. Intelligent control of in-wheel motors in a vehicle with analytical determination of torque distribution: (Content №4 2026); ... Applied Energy, 384, 125462. https://doi.org/10.1016/j.apenergy.2025.125462 14. Kou, L., Sysyn, M., Liu, J., Fischer, S., Nabochenko, O., & He, W. (2023). Prediction system of rolling contact ...; Created on 24 August 2026
6. Phase composition of multicomponent aluminum bronzes criteria-based evaluation (Part 1. Supersaturated copper α-matrix and phase composition of Cu–Al–X system multicomponent bronzes stability criteria): (Content №4 2026); ... Senkov, O. (2018). About the Reliability of CALPHAD Predictions in Multicomponent Systems. Entropy, 20(12), 899. https://doi.org/10.3390/e20120899 24. Tolborg, K., Klarbring, J., Ganose, A. M., ...; Created on 24 August 2026
7. Three-dimensional numerical analysis of rock deformation in underground mining excavations ‒ Boukhadra iron mine (Algeria): (Content №4 2026); ... (46), 48-68. https://doi.org/10.1016/j.compgeo.2012.05.013 11. Alkhdour, A., Radkevych, A., Tiutkin, O., & Bondarenko, N. (2020). Prediction of the stress-strain state of circular workings in ...; Created on 24 August 2026
8. Wireframe modeling to optimize open-pit parameters of Boguty tungsten deposit (Kazakhstan): (Content №4 2026); ... 12. Xu, C., Zhou, K. P., Xiong, X., Gao, F., & Lu, Y. (2023). Prediction of mining-induced subsidence by sparrow search algorithm with extreme gradient boosting and TOPSIS method. Acta Geotechnica, ...; Created on 24 August 2026
9. Analysis of labor productivity in the context of technological transformations: (Content №3 2026); ... of automating prediction. Journal of Economic Perspectives, 33(2), 31-50. https://doi.org/10.1257/jep.33.2.31 8. Babina, T., Fedyk, A., He, A. X., & Hodson, J. (2024). Artificial intelligence, firm ...; Created on 26 June 2026
10. Investigation of the accuracy of underground control surveying networks through the application of neural network modeling: (Content №3 2026); ... of the farthest point in the network was detected, and the probability of failure-free operation of the UMSCN was estimated at 71 %. The proposed approach improves the reliability of accuracy predictions ...; Created on 26 June 2026
11. Model for improving the reliability of microservice software during the functional testing phase: (Content №3 2026); ... & Yin, H. (2019). Failure Rate Prediction Model of Substation Equipment Based on Weibull Distribution and Time Series Analysis. IEEE Access, 7, 85298-85309. https://doi.org/10.1109/access.2019.2926159 ...; Created on 26 June 2026
12. Nonparametric homogeneity criterion for selective formation of an ensemble of time series segments: (Content №3 2026); ... from https://ieeexplore.ieee.org/document/11184472 10. Liang, X., Zhang, L., & Zhao, J. (2025). AT-LSTM-CUSUM Digital Intelligent Model for Seepage Safety Prediction of Concrete Dam. Structural ...; Created on 26 June 2026
13. Implementation of ecological innovations in Ukrainian industry: current trends and challenges: (Content №3 2026); ... (2025). Robust Gas Demand Prediction Using Deep Neural Networks: A Data-Driven Approach to Forecasting Under Regulatory Constraints. Energies, 18(14), 3690. https://doi.org/10.3390/en18143690 14. State ...; Created on 26 June 2026
14. Relationship between unconscious hazard and perceived safety in organizational management systems: (Content №3 2026); ... F.J., Silla, I., & Martínez-Córcoles, M. (2023). The role of empowering leadership, safety culture and safety climate in the prediction of mindful organizing in an air traffic management company. Safety ...; Created on 26 June 2026
15. Impact of temperature variations on soil-foundation interface behavior: (Content №3 2026); ... 36(1), 49-62. 15. Laman, M., & Uncuoglu, E. (2009). Prediction of the moment capacity of pier foundations in clay using neural networks. Kuwait Journal of Science and Engineering, 36, 1-20. ...; Created on 26 June 2026
16. Data-driven LSTM-based control to replace PID for unknown-model electric motor systems: (Content №2 2026); ... https://doi.org/10.1177/00202940241229927 15. Teler, K., & Orlowska-Kowalska, T. (2023). Analysis of the stator current prediction capabilities in induction motor drive using the LSTM network. ...; Created on 25 April 2026
17. Software-based evaluation of pseudorandom frequency-hopping for wireless infocommunication cybersecurity: (Content №2 2026); ... Machine Learning Based Prediction of Frequency Hopping Spread Spectrum Signals. 2023 IEEE 34 th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 1-6. Toronto. ...; Created on 25 April 2026
18. Methodology for assessing the condition of power plant units using digital twin models: (Content №2 2026); ... enhanced nuclear reactor power prediction. Energy and AI, 19, 100450. https://doi.org/10.1016/j.egyai.2024.100450 6. Prokhorova, V., Budanov, M., & Budanov, P. (2024). Devising an integrated methodology ...; Created on 25 April 2026
19. Justification of a rational scheme for configuring soil-treating machinery: (Content №2 2026); ... Ji, C., Nyalala, I., Sunusi, I. I., & Opiyo, S. (2021). Prediction of precise subsoiling based on analytical method, discrete element simulation and experimental data from soil bin. Scientific Reports, ...; Created on 25 April 2026
20. Modeling of basalt tuff beneficiation by dry high-intensity magnetic separation: (Content №2 2026); ... of magnetic impurities, and prediction of process efficiency based on magnetic field induction. The obtained regression relationships can be applied in the design and optimization of preliminary beneficiation ...; Created on 25 April 2026

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