Artificial Intelligence at IgMin Research | Engineering Group

Artificial Intelligence (AI) has been considered a revolutionary and world-changing science, although it is still a young field and has a long way to go before it can be established as a viable theory. Every day, new knowledge is created at an unthinkable speed, and the Big Data Driven World is already upon us. AI has developed a wide range of theories and software tools that have shown remarkable success in addressing difficult and challenging societal problems. However, the field also faces many challenges and drawbacks that have led some peo...ple to view AI with skepticism. One of the main challenges facing AI is the difference between correlation and causation, which plays an important role in AI studies. Additionally, although the term Cybernetics should be a part of AI, it was ignored for many years in AI studies. To address these issues, the Cybernetic Artificial Intelligence (CAI) field has been proposed and analyzed here for the first time. Despite the optimism and enthusiasm surrounding AI, its future may turn out to be a “catastrophic Winter” for the whole world, depending on who controls its development. The only hope for the survival of the planet lies in the quick development of Cybernetic Artificial Intelligence and the Wise Anthropocentric Revolution. The text proposes specific solutions for achieving these two goals. Furthermore, the importance of differentiating between professional/personal ethics and eternal values is highlighted, and their importance in future AI applications is emphasized for solving challenging societal problems. Ultimately, the future of AI heavily depends on accepting certain ethical values.Read more

The operating experience of mechanical seals shows that as a result of angular deformations of the rings, the wear of the contact surfaces along the radius is uneven. When designing mechanical seals, it is necessary to calculate the amount of expected leakage through the seal, friction power consumption, as well as the possible durability of the unit. These calculated dependencies and estimates are obtained based on the constructed mechanical seal model. In the area of hydrodynamic load support in the case of a confusor joint or a converging fi...lm, the slope of the pressure diagram is such that a decrease in the film thickness increases the hydrodynamic support. This is referred to as enabling stable non-contact sealing operation. The execution of the rubbing surfaces of the interface of the end pair should ensure the formation of the calculated confusor shape of the sealing gap in all modes of operation and axisymmetric pressure fields during the rotation of the rotor.Read more

This paper tackles the vital issue of missing value imputation in data preprocessing, where traditional techniques like zero, mean, and KNN imputation fall short in capturing intricate data relationships. This often results in suboptimal outcomes, and discarding records with missing values leads to significant information loss. Our innovative approach leverages advanced transformer models renowned for handling sequential data. The proposed predictive framework trains a transformer model to predict missing values, yielding a marked improvement i...n imputation accuracy. Comparative analysis against traditional methods—zero, mean, and KNN imputation—consistently favors our transformer model. Importantly, LSTM validation further underscores the superior performance of our approach. In hourly data, our model achieves a remarkable R2 score of 0.96, surpassing KNN imputation by 0.195. For daily data, the R2 score of 0.806 outperforms KNN imputation by 0.015 and exhibits a notable superiority of 0.25 over mean imputation. Additionally, in monthly data, the proposed model’s R2 score of 0.796 excels, showcasing a significant improvement of 0.1 over mean imputation. These compelling results highlight the proposed model’s ability to capture underlying patterns, offering valuable insights for enhancing missing values imputation in data analyses.Read more