The article discusses the problem of feature selection when training machine learning (ML) models in the task of identifying fake (phishing) websites. As a solution, a set of key metrics is proposed: efficiency, reliability, fault tolerance, and retrieval speed. Efficiency measures impact of feature to prediction accuracy. Reliability measures how well feature distinct phishing from legitimate. Fault tolerance score measures empirical probability of feature to be valid and fulfilled. And retrieval speed is logarithmic time of feature extraction. This approach allows for the ranking of features into categories and their subsequent selection for training machine learning models, depending on the specific domain and constraints. In this article, 82 features was measured, and 6 fully-connected neural networks was trained to evaluate the effectiveness of metrics. Experiments has shown that proposed approach can increase the accuracy of models by 1-3%, precision by 0.03, and significantly reduce overall extraction time and so improve response rate.

Keywords: feature evaluation method, machine learning model, identification of phishing websites, metric, efficiency, reliability, fault tolerance, and retrieval speed

The article discusses the possibility of using the ANSYS WORKBENCH software package to calculate the uneven settlement of building foundations. The heterogeneity of the physical and mechanical properties of the soil, the difference in the thickness of the bearing layer and other factors lead to uneven development of settlement. This causes the appearance of cracks in the supporting structures, and in the worst case, the destruction of part of the building or the building as a whole. Methods for calculating settlements are very complex, but using the capabilities of modern computers and computer simulation programs makes it possible to obtain a simple and accurate solution to such problems. To evaluate the deformations of the foundation on heterogeneous soils the ANSYS software package was be used. The proposed method can be used to quantify the uneven settlement of the foundations of real buildings and structures.

Keywords: ANSYS WORKBENCH, foundation, uneven settlement, skew, computer modeling, deformation, finite element method

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