The article develops a model for monitoring and predicting the characteristics of data warehouses. We give the problem statement and form a system of nonlinear differential equations is formed that allows for the analysis of the dynamics of data warehouse quality characteristics. Professionals can use the results of this study to monitor and predict the performance of data warehouses in large-scale systems.

A method for restoration of a network distribution system damaged by an unfriendly impact is considered. The peculiarity of the method is the application of limit graphs to the solution of the restoration problem and the possibility of finding various optimization solutions taking into account the time and cost of work, the power shortage of sources, the number of switching operations of commutators, and others. The description of the method and restoration operations is given, taking into account the category of consumers. The assessment of the technical stability of the power distribution system is carried out on the example of a network fragment. The proposed approach can be used to formulate recommendations for improving the stability of infrastructure systems and to support the decision maker in real conditions of unfavorable factors.

The problem of estimating the fundamental frequency of a harmonic series arises in many areas of science and technology. For example, in vibration diagnosis, it is required to estimate the wear of bearings by the shift of the base of a harmonic series. In audio signal processing, this problem is associated with automatic instrument tuning. In speech synthesis, the fundamental frequency determines the pitch. In speech recognition, the frequency of the fundamental tone is an important information feature. In radio engineering, this problem is solved for the purpose of signal restoration, filtering, and decoding. In biomedical engineering, when analyzing a patient’s ECG, EEG, voice, or breathing, pathologies such as arrhythmia are diagnosed by the fundamental frequency. In the detection and classification of sea vessels, the most significant information criterion is the base of a propeller shaft–blade harmonic series. This paper proposes new approaches to estimating the fundamental frequency in high noise conditions. To reduce errors, the idea is to use the method of periodograms, filtering, autocorrelation, and the Hilbert transform. Note that in high noise conditions, the estimate of the fundamental frequency of a harmonic series is significantly improved by selecting optimal parameters: the size of the time window, filtering parameters, the spectrum interval for autocorrelation, and the number of autocorrelations.

In this work, we explore the possibilities of improving the characteristics of mobile robots based on wheeled vehicles, using the optimization of their movement along the route, taking into account kinematic characteristics and constraints. To do this, after selecting an array of waypoints and approximating it with splines, we divide the path into relatively linear segments and segments with significant maneuvering, for which we calculate the curvature profile. Further, during the movement, the predictive control module of the robot controller uses this curvature profile as a reference path, and to measure the current curvature, we use the microwave sensors of the wheels of the robot's differential drive.

This paper provides a brief overview and analysis of the most commonly used methods for assessing information security risks in various complex systems. These methods involve creating specific models that help assess, manage, and predict the possible occurrence of adverse situations related to information security. These methods help to make decisions aimed at minimizing the potential damage that could occur because of external attacks on information resources or other threats that exploit existing vulnerabilities. However, they provide an acceptable result in risk assessment in conditions where it is possible to quantify the parameters on which the risk depends. In conditions of high uncertainty, for example, when determining the dependence of risk on subjective factors, the use of these methods can lead to high errors. As a rule, risk assessment is associated with a high degree of uncertainty of parameter values and their mutual influence on the information security risk level. The method proposed by the authors, based on the combined use of fuzzy logic and regression analysis, makes it possible to assess the information security risk in conditions of uncertainty in complex information systems with a network structure. This method also allows you to identify the parameters that most influence the risk level, which in turn enables you to protect information resources while optimizing the cost of implementing an effective protection system. Using this method and basing on the predicted risk level values, allows you to plan events to improve the level of information system protection in both the short and long term.