This article is devoted to solving the problem of manufacturing products from carbon fiber composite materials, which are obtained as a result of layer-by-layer laying of carbon fiber with impregnation of their binder components. This paper presents a description of the process of spiral winding of products on a cylindrical mandrel and the mathematical model, which takes into account the coefficient of friction and the necessary reverse zones in which the tape will not slip. The model is implemented as a Python program and is capable of simulating and visualizing the step-by-step winding of a carbon tape on a cylindrical surface. It is possible to optimize the friction coefficient to ensure the tightest winding of subsequent passes. The program takes into account reverse zones, which are calculated taking into account the friction coefficient of the cylindrical mandrel. Based on the simulated winding process, a control program for the robotic arm is generated. The performance of the proposed model and its implementation was tested on a test bench with a robot.

The paper discusses sentences with coordinating conjunctions and homonymy where it is hard or impossible to build feasible syntactic structures using well-known models – dependency-based parse trees, constituency-based parse trees, and syntactic groups model. We suggest an approach to represent syntactic structures of sentences with conjunctions. We present features which distinguish our approach from the models under investigation. The paper shows multiple ways of visualization of syntactic structures. We illustrate how homonymy influences parsing and give examples of lexical and syntactic homonymy. We show the need to represent homonymy explicitly and suggest an approach to homonymy representation in morphological and syntactic structures.

In this paper, we consider the problem of image preprocessing for further pattern recognition through the use of a multiagent neurocognitive architecture. The solution to this problem is achieved using the breadth-first search (BFS) method. The article presents algorithmic descriptions of the segmentation method and the image processing method in a multiagent neurocognitive architecture. Experiments were carried out on object recognition in a segmented image based on a multi-agent neurocognitive architecture.

The article explores the principles of organizing warehouse systems based on standardized transport and storage cells. It discusses the general hardware features of transport and storage cells that enable the movement of stored goods between them. The article presents a method for constructing a warehouse graph that takes into account possible directions for transferring containers with cargo between the transport and storage cells integrated into the warehouse structure, along with their common hardware characteristics. Key criteria used in determining the edge weights of the graph are described, including the basic cost of movement for each axis, cell wear and tear, cargo weight, fragility of the cargo, distance to the nearest available cells, and repairability. Algorithms are presented, the primary task of which is to determine the sequence of container movements between warehouse cells to facilitate loading and unloading operations. Simulation modeling of a warehouse with dimensions of 5×5×5 was conducted using the proposed algorithms, both with and without considering cell wear and tear parameters. The results of the simulation highlighted the significance of this criterion, allowing for extended warehouse servicing intervals and maximizing the time until the first failure.The study also investigates the possibility of optimizing the structure of such warehouse systems to meet various requirements. As part of this investigation, the structure was optimized for a warehouse with dimensions of 4×3×3.

Currently, Russia is moving towards automating the collection of information from metering devices for heat, gas, water, electricity, etc. Technologies are being developed that allow transmitting data on resource consumption through various communication channels, both wired and on-air. There are already devices and devices that allow transmitting readings of electricity metering devices over existing wired communication networks, and this issue is being resolved at the legislative level, federal Law No. 522-FZ of 01.07.2020 has been adopted. The basis for the research is to save time and effort to obtain the necessary information to take into account the readings of electricity from substations, increase the speed of decision-making, to be able to predict the situation with big data to identify abnormal values and eliminate them (for example, identified data from electricity meters will reduce the time labor costs of accounting operators and economic losses of the energy supply company). The article proposes software methods for detecting data on electricity losses based on the use of artificial neural network algorithms and allowing to detect inconsistencies of commercial data readings of electric meters, which will reduce the commercial component of electricity losses. A verification calculation of an artificial neural network was performed for inconsistencies in the data on the transmitted electricity.