The article presents an ontological model of a control system for a Peltier thermoelectric element. The ontology describes the structure of the system by identifying objects, transformation processes within these objects, and the attributes of the relationships between them. Based on the developed ontological model, a cascade control system has been designed, integrating a PID controller, a fuzzy-digital filter, and an exponential-averaging filter, with its cognitive behavior governed by fuzzy logic rules. Improvement of the dynamic characteristics of transient processes in the Peltier element control system is achieved through the application of the mathematical and ontological solutions specified in the model. The cascade control system reduces the amplitude of the first harmonic of the control signal by 12% and decreases the transient response time by 31.9%.

The Central Sikhote-Alin Fault (CSAF) is one of the largest tectonic structures in the continental part of the south of the Russian Far East. Its modern geodynamic activity is still very poorly understood, especially by remote sensing methods. The available geological estimates of movements along the CSAR reach several mm/year, however, the available scattered modern geodetic data allow us to state that no displacements exceeding a few mm/year have been detected in the central part of the fault.

In the present work, based on the data of GNSS observations carried out in the first two decades of the 21st century, the first quantitative estimates of the secular (plate) movements of the Earth's crust in the vicinity of the village of Kievka (Primorsky Krai), located at the southern end of the CSAR, are obtained. Also, in the study area, numerical modeling of the effect of geoenvironment disturbances (co- and postseismic displacements) initiated by the catastrophic Tohoku earthquake on March 11, 2011, Mw 9.1, was evaluated and performed. The results obtained are in good agreement with the available models of the earthquake source and models of postseismic viscoelastic relaxation of the geoenvironment.

The article is devoted to the development of a scientific and methodological apparatus for improving the effectiveness of protecting digital platforms from cyber threats by creating processing and detection algorithms that take into account the cognitive characteristics of users. A conceptual model of a three-stage protection system is proposed, integrating technical security mechanisms with cognitive decision-making models. A heuristic detection algorithm based on Random Forest machine learning with analysis of 47 features, including technical URL characteristics and cognitive-semantic content characteristics, has been developed. A methodology for dynamic integration of four threat data sources has been created, reducing response time from 12–14 hours to two hours. An algorithm for recursive analysis of redirection chains up to ten levels deep to detect masked threats is proposed. Experimental validation on an empirical base of approximately one million records confirmed detection accuracy of 87% when processing one hundred thousand records per hour. The developed solutions ensure compliance with the requirements of GOST R 57580.1-2017 and Russian legislation in the field of personal data protection.

The paper proposes an approach to multi-criteria decision support based on a cognitively oriented multi-agent information-analytical system. Cognitive modeling methods are developed, including a formal ontological representation of knowledge about production planning and a coalition–holonic agent architecture that ensures adaptability and transparency of computations. A hybrid evolutionary multi-criteria algorithm is introduced, in which agents generate alternative plans at the local level using a parallel genetic algorithm that optimizes a combination of several criteria. At the global level, a multi-stage selection of alternatives is implemented with filtering of resource overloads and similar solutions, followed by final aggregation using the PROMETHEE and ELECTRE multi-criteria decision-making methods.

An experimental study is carried out comparing manual planning with planning supported by the developed system, as well as analyzing the impact of dynamic adaptation of the genetic algorithm parameters. The results show that the use of the system makes it possible to reduce plan generation time by a factor of 20–30 while maintaining or improving solution quality. At the same time, resource overloads are completely eliminated, and early termination of evolutionary computations is ensured without loss of solution quality. The system and proposed algorithms are intended for use in planning project activities at manufacturing enterprises.

This article addresses the problem of creating dynamic narrative systems for video games with real-time interactivity. It presents the development and testing of a GPT integration component for dialogue generation, which revealed a critical limitation of cloud-based solutions – a 30-second latency unacceptable for gameplay. A hybrid architecture of an adaptive system is proposed, combining LLMs with reinforcement learning mechanisms. Particular attention is given to solving the problems of game world consistency and managing long-term context of NPC interactions through a RAG approach. The transition to the Edge AI paradigm with the application of quantization methods to achieve a target latency of 200–500 ms is substantiated. Metrics for evaluating personalization and dynamic content adaptation have been developed.

The technology of modelling various situations in virtual environment systems, which are computer three-dimensional models of a real or artificial environment, is discussed. The user can view these scenes directly on the computer screen, wall screen, in a stereo glasses, virtual reality glasses, etc. He can also move inside a virtual scene and interact with its objects. In turn, the environment can also change. This allows modelling of various situations (situation modelling) in the virtual environment system. With such modelling, some static or dynamic situation is set in the virtual environment system in which the operator must perform the tasks assigned to him.

A mechanism for setting situations by changing a virtual three-dimensional scene using configuration files and virtual control panels is proposed. A special language has been developed for writing configuration files, and a special editor has been developed for creating virtual control panels. The approbation of the proposed methods is presented on the examples of two virtual scenes: a training ground for mobile robots and a jet backpack for the rescue of an astronaut in outer space.

The paper presents a comparative analysis of methods for representing three-dimensional objects to perform real-time Boolean operations in the Unity game engine environment. Four main approaches are considered: polygonal representation based on constructive solid geometry (CSG), sign distance functions (SDF), voxel methods and CAD-systems with boundary representation (B-Rep) and NURBS-surfaces.

An experimental study of the performance of polygonal algorithms of Boolean operations and SDF functions based on ray marching implementation is carried out. It is revealed that polygonal methods are characterized by high initial system construction costs, but provide stable performance during long operations and preservation of transformation results. SDF functions demonstrate high speed of operations and flexibility in creating smooth transitions between objects, but are limited in application for long-term tasks due to the peculiarities of the computational model.

The areas of effective application of each approach are identified: polygonal methods are recommended for tasks requiring precise geometric control and integration with traditional graphics pipelines, while SDF functions are optimal for procedural generation, multilayer material rendering and creation of dynamic visual effects. The results of the study can be used in the development of interactive simulators, game applications and virtual reality systems.

The materials presented at the Conference describe the results of recent years in the following areas: Open access to scientific data and knowledge in Earth Sciences; Data peculiarities in Earth Sciences: new concepts and methods, tools for their collection, integration and processing in different information systems, including systems with intensive use of data; Data mining and mathematical simulation of natural processes in Earth Sciences. Evolution of classical GIS-applications in Earth Sciences; Application to Critical Raw Materials (CRM); social aspects of mining (e.g., the Social Licence to Operate [SLO]); predictive mapping and applications to exploration, landuse and search for extensions of known deposits; Intelligent data analysis, elicitation of facts and knowledge from scientific publications. Thesauruses, ontologies and conceptual modeling. Semantic WEB, linked data. Services. Content semantic structuring. Applications for geosciences, e.g., Ontology-based Dynamic Decision Graphs for Expert systems and decision-aid tools; Application of methods and technologies of the remote sensing in Earth Sciences: from satellites to unmanned aerial vehicles; Information technologies for demonstration and popularization of scientific achievements in Earth Sciences; Applications: environmental risks including mining wastes, natural hazards, water resource management, etc.