A statistical analysis of the multimodal ENERGI (ENgagement and Emotion Russian Gathering Interlocutors) data corpus containing audio-video recordings of communication in Russian by a group of people obtained using the Zoom teleconference system has been performed. The corpus data is annotated into three classes: participant engagement (high, medium, low), emotional arousal (high, medium, low), and emotional valence (positive, neutral, negative), as well as ten classes of communicative gestures. The corpus contains 6.4 hours of video recordings of group communications, with a total of 18 unique speakers; the data is annotated using 10-second time intervals. ENERGI’s advantages over other corpora include its multimodality, Russian language support, speaker diversity, natural recording conditions, and extensive annotation across several behavioral parameters of communication participants. The corpus can be used to develop a multimodal automated system for analyzing the behavioral aspects of participants in virtual group communications.

The basics of building automated information systems (IAS) for integrated modeling of complex distributed natural objects in solving problems of integral assessment of forest ecosystems stability are considered. When creating such systems, it is proposed to use the basic principles of the qualimetry of models and polymodel complexes. This approach allows to find ways to solve the main problems of complex modeling in the integrated assessment of sustainability: determining the required composition of partial models for calculating individual indicators; selection and adaptation of models, taking into account the necessary composition of the source data; formation of algorithms for calculating integral indicators. A comparative analysis shows that it is advisable to use container management systems in combination with elements of a multiservice architecture as the technological basis of IAS. An architecture of the integrated modeling IAS is proposed, which includes components for obtaining integral estimates using multicriteria analysis algorithms, calculation modules for private indicators, components for obtaining and analyzing the necessary heterogeneous source data, including ground data and remote sensing data, as well as means for orchestrating and ensuring the coordinated functioning of the IAS. The use of the proposed architecture makes it possible to perform modeling within a single distributed, scalable information and computing environment.

The basic requirements for modern educational computer software models are analyzed.An emulator of a digital computer learning processor is proposed, which is a new-generation software model developed in accordance with modern requirements.The results of a comparative analysis of software models currently used in the educational process in the training of IT specialists are presented. The proposed emulator is an innovative development that meets modern requirements for educational software models and,as a comparative analysis has shown, is functionally superior to other software models.

The problem of synthesizing reactive, time-optimal control for quadcopters is aggravated by their multifaceted, underactuated dynamics and the complexity of solving boundary-value problems in real time. This work addresses these challenges, presenting a reinforcement learning framework that learns to autonomously navigate in collision-free environments with optimal waypoint-reaching policies. Our contributions include a cascaded actor architecture inspired by position-velocity separation in classical control to improve flight stability and smooth actions, as well as a composite reward function incorporating radial velocity and acceleration components, promoting maximal progress toward targets and steering the agent toward bang-bang-like maneuvers. Quantitative comparisons prove that our agent achieves smooth control actions, leading to optimal trajectories that adhere tightly with minimal deviations to the desired path.

This paper proposes new methods for multi-agent formation control during coordinated following of straight and circular paths. The dynamics of the agents are described using a nonholonomic model, which is a universal approach suitable for a wide range of robotic platforms. The task of the agents is to follow given straight and circular paths while simultaneously maintaining a desired geometric formation. A formation control algorithm based on the leader–follower strategy is developed, ensuring coordinated agent motion and preservation of the specified formation. In addition, a fully distributed control algorithm is proposed, which does not require a leader and relies solely on local information from neighboring agents. For each algorithm, the stability of the desired formation is analyzed. The effectiveness of the proposed algorithms is validated through numerical simulations in MatLab.

The representation of dynamical systems in the form of bond graphs, which make it possible to unify a modular approach to modeling multi-domain physical systems described by laws from various fields of physics, such as mechanics and hydraulics, is considered. Based on multiconnected or vector bond graphs, a library of mechatronic system elements, which accelerates the process of building models and reduces the likelihood of errors, is been developed in MatlabSimulink environment. The structure of the developed library and its main elements, which make it possible to describe systems of several bodies and simulate their motion in various reference frames, are discussed. An example of using the library for modeling a specific mechanical system is given.

Experimental results of a study of the effect of ionizing radiation with different dose rates on fiber-optic systems using fibers with a germanosilicate core (GeO₂) and an undoped pure silica core (SiO₂) are presented. A mathematical approximation of the experimental curves for the growth of radiation-induced optical losses in the fiber is performed using a modified power-law equation that includes the contribution of the ionizing radiation dose rate. A correlation between the values of empirical coefficients and the dose rate of ionizing radiation is experimentally established. A natural logarithmic function equation is proposed for describing the dependence of the empirical coefficients defining the shape of the radiation-induced loss growth curve on the dose rate. An approach to reconstructing the radiation-induced loss growth curve using equations for the dependence of the empirical approximation coefficients on the dose rate is proposed; this technique enables predicting the radiation response of the optical fiber under new conditions without experimental setup. The method demonstrates applicability for single-mode fibers with silica and germanosilicate fiber cores of different designs. Based on the described approach, a methodology is developed for determining correlation equations for empirical coefficients.

The current tasks of monitoring and diagnostics of equipment for optimal management of oil production and oil treatment are discussed. To solve these problems, it is necessary to create a fleet of reliable measuring instruments based on automated software and measurement systems (SMS) with diagnostics of measuring equipment without stopping its operation. The formation of a common fleet of measuring instruments can be performed on the basis of a proton magnetic resonance (PMR) relaxometer as part of a rapid flow PMR analyzer, combining in one device the possibilities of self-diagnosis, measurement of many oil parameters and effective control of wells and equipment. Methods of selfdiagnosis of relaxation meter elements and SMS blocks based on relaxation parameters of PMR affected by additive and multiplicative noise are presented. Algorithms and programs for self-diagnosis of analyzer elements and blocks have been developed, as well as methods for measuring oil characteristics, including such an important parameter as total sulfur content, which negatively affects oil quality and equipment safety. Methods and algorithms for diagnostics of its elements without stopping the equipment for noise analysis and deviation of individual parameters of PMR sensors are proposed.

The method, its implementing device, and software have been improved, collectively designed to study the stages of the extraction process of target components from porous materials in real time. The updated software enables the determination of optimal operating modes and conditions for extraction processes, closely resembling actual process conditions. The proposed development can be used to study processes involving changes in the mass and/or volume of the porous solid being studied while suspended in a liquid.

The possibility of using noise diodes in the implementation of the thermo-anemometer method is evaluated. Noise diodes of the ND102L and ND103L models produced in Belarus are selected as objects of research. An increase in the supply voltage of the noise diode leads to an increase in the repetition rate of the noise pulses to a certain value. In the overvoltage range from -0.20 to 0.40 V for ND102L and from -0.09 to 0.70 V for ND103L, there is an increase in the frequency of noise pulses, which at a temperature of 293 K takes the highest value: 455 kHz for ND102L and 1014 kHz for ND103L. Thus, changing the overvoltage applied to the noise diode in these intervals allows to adjust the frequency of occurrence of noise pulses. It is shown that with a constant value of the supply voltage of the noise diode and an increase in temperature, the frequency of occurrence of noise pulses generated on the load decreases. The temperature dependence of the frequency of noise pulses is more pronounced for ND103L than for ND102L. A thermo-anemometer method for determining the velocity of air flow propagation based on noise diodes is proposed. The method allows to register the minimum value of the air flow velocity of 0.2 m/s for both studied models of noise diodes. The time to set the temperature is 30 seconds after the start of exposure to the air flow.

The key challenges of creating a part manufacturing route during production preparation are identified. A method for creating a processing route taking into account the current and planned capabilities of the equipment and creating an optimal sequence of operations through the use of an intelligent enterprise resource planning system is proposed.