A new approach to increasing the efficiency of extreme control systems by improving the method of searching for the extremum of the objective function is presented. In its multidimensional nonlinear optimization, instead of a traditional linear search along a once selected direction, an exploratory search is used, the direction of which at each step is adapted to the topology of the objective function. This makes it possible to localize an extremum as quickly as possible and significantly reduce the time of its determination. An algorithm for interpolation search for an extremum in the found interval is proposed. The objective function is modeled by a cubic spline segment based on information about its gradient vector at the boundary points of the interval, as a result of which the number of interpolation search steps is significantly reduced. The possibility of simplified nonsmooth interpolation using first-order splines in the extremum region is considered. The results of a numerical experiment confirm the high efficiency of the new method in solving various problems.

Keywords: extremal control systems, nonlinear optimization, acceleration of extremum search, quasi-Newton method, polynomial interpolation, non-smooth interpolation

In this experiment, a solver (NEAT) and a simulator (an inverted pendulum cart object) are implemented, where the solver will influence the object in order to keep it in a stable state, i.e. don't let the pendulum fall. The main objective of the experiment is to study the possibility of implementing a simulator of a real physical object and use it to determine the target function of the neuroevolutionary algorithm NEAT. Solving this problem will make it possible to implement controllers based on the NEAT algorithm, capable of controlling real physical objects.

Keywords: machine learning, non-revolutionary algorithms, genetic algorithms, neural networks

The article examines the situation that emerged as a result of the higher education reform of 2006-2012. in Russia there is a modern organizational and territorial structure of university campuses, which has different types of spatial and territorial location: urban local campus, urban dispersed campus, suburban local campus, mixed. Thus, almost all federal universities are located on several campuses within the territory of the city where they are located, and several of them have campuses in several cities. Some existing classifications of university campuses according to various criteria are considered and their insufficiency for a complete scientific description of modern campuses is revealed. The existing classification by spatial location relative to the city territory is supplemented by such types as regionally dispersed campus and locally dispersed campus. The supplemented classification reflects the current situation in the Russian Federation and allows for a scientific description of modern university campuses in Russia, taking into account their organizational and territorial specifics.

Keywords: classification, university campus, organizational structure, territorial structure, locally dispersed campus, regionally dispersed campus

The article presents the results of a comprehensive assessment of the deformability of a frame one-story, single-span building, the load-bearing structures of which are made of laminated wood. Constant and short-term loads were applied to the frame elements, the duration fraction was identified, the standard value was clarified, and the values of vertical displacements of the structural units were obtained. An assessment was made of the maximum deflections of the circuit elements from the standard load values with the maximum permissible valuese considered - on columns and in floor beams.

Keywords: one-story single-span building, permanent loads, short-term loads, standard load values, laminated board package, spacer system, boundary conditions, modulus of elasticity, stiffness, stress, displacement, CAD

The article examines the influence of various superplasticizers on the performance characteristics of concrete. A series of tests of samples-beams of fine-grained concrete modified with plasticizers of various types was carried out. The optimal amount of the introduced additive was experimentally determined to compare the plasticizing effect of the cement-sand mixture. Experimental data are given indicating the main operational characteristics of the material depending on the additive used. The most effective additive "Polyplast SP-3" has been determined.

Keywords: concrete, fine-grained concrete, mixture, lignosulfonates, polycarboxylates, naphthalene sulfonates, plasticizer, superplasticizer, water demand, plasticity

Roads have a huge impact on the life of a modern person. One of the key characteristics of the roadway is its quality. There are many systems for assessing the quality of the road surface. Such technologies work better with high-resolution images (HRI), because it is easier to identify any features on them. There are a sufficient number of ways to improve the resolution of photos, including neural networks. However, each neural network has certain characteristics. For example, for some neural networks, it is quite problematic to work with photos of a large initial size. To understand how effective a particular neural network is, a comparative analysis is needed. In this study, the average time to obtain the HRI is taken as the main indicator of effectiveness. EDSR, ESPCN, ESRGAN, FSRCNN and LapSRN were selected as neural networks, each of which increases the width and height of the image by 4 times (the number of pixels increases by 16 times). The source material is 5 photos of 5 different sizes (141x141, 200x200, 245x245, 283x283, 316x316) in png, jpg and bmp formats. ESPCN demonstrates the best performance indicators according to the proposed methodology, the FSRCNN neural network also has good results. Therefore, they are more preferable for solving the problem of improving image resolution.

Keywords: comparison, dependence, effectiveness, neural network, neuronet, resolution improvement, image, photo, format, size, road surface

Road surface quality assessment is one of the most popular tasks worldwide. To solve it, there are many systems, mainly interacting with images of the roadway. They work on the basis of both traditional methods (without using machine learning) and machine learning algorithms. To increase the effectiveness of such systems, there are a sufficient number of ways, including improving image quality. However, each of the approaches has certain characteristics. For example, some of them produce an improved version of the original photo faster. The analyzed methods for improving image quality are: noise reduction, histogram equalization, sharpening and smoothing. The main indicator of effectiveness in this study is the average time to obtain an improved image. The source material is 10 different photos of the road surface in 5 sizes (447x447, 632x632, 775x775, 894x894, 1000x1000) in png, jpg, bmp formats. The best performance indicator according to the methodology proposed in the study was demonstrated by the "Histogram equalization" approach, the "Sharpening" method has a comparable result.

Keywords: comparison, analysis, dependence, effectiveness, approach, quality improvement, image, photo, format, size, road surface

This paper considers the conditions and factors affecting the security of information systems functioning under network reconnaissance conditions. The developed model is based on the techniques that realize the dynamic change of domain names, network addresses and ports to the network devices of the information system and false network information objects functioning as part of them. The formalization of the research problem was carried out. The theoretical basis of the developed model is the theories of probability and random processes. The modeled target system is represented as a semi-Markov process identified by an oriented graph. The results of calculation of probabilistic-temporal characteristics of the target system depending on the actions of network reconnaissance are presented, which allow to determine the mode of adjustment of the developed protection measures and to evaluate the security of the target system under different conditions of its functioning.

Keywords: departmental information system, network intelligence, structural and functional characterization, false network information object

The current legislative acts and regulatory and technical documents defining the requirements for the organization of the customer's activities are considered in the work. A review of studies with different approaches to the formation of organizational structures of the customer, depending on the types of construction, their volumes and features of objects, is carried out. The factors determining the requirements for the formation of organizational structures of the customer for various objects are highlighted.

Keywords: construction organization, technical customer, organizational structure, construction control, project approach

The purpose of the study is to improve the efficiency of Dijkstra's algorithm by using the shared memory model with OpenMP library and working on the principle of parallel execution in the implementation of the algorithm. Using Dijkstra's algorithm to find the shortest path between two nodes in a graph is quite common. However, the time complexity of the algorithm increases as the size of the graph increases, resulting in longer execution time, so parallel execution is a good option to solve the time complexity problem. In this research work, we propose a parallel computing method to improve the efficiency of Dijkstra's algorithm for large graphs.The method involves dividing the array of paths in Dijkstra's algorithm into a specified number of processors for parallel execution. We provide an implementation of the parallelized Dijkstra algorithm and access its performance using actual datasets and with different number of nodes. Our results show that Dijkstra's parallelized algorithm can significantly speed up the process compared to the sequential version of the algorithm, while reducing execution time and continuously improving CPU efficiency, making it a useful choice for finding shortest paths in large graphs.

Keywords: Dijkstra algorithm, graph, shortest paths, parallel computing, shared memory model, OpenMP library

It is estimated that more than 9% of the Russian population is hearing impaired, and the development of dactyl recognition systems is becoming critical to facilitate their social communication. The introduction of dactyl recognition systems will improve communication for these people, providing them with equal opportunities and improving their quality of life. The research focused on learning the characters of the dactyl alphabet, as well as developing a labeled dataset and training a neural network for gesture recognition. The aim of the work is to create tools capable of recognizing the signs of the Russian dactyl alphabet. Within the framework of this research the method of computer vision was applied. The process of gesture recognition consists of the following steps: first the camera captures the video stream, after the images of hands are preprocessed. Then a pre-trained neural network analyzes these images and extracts important features. Next, gesture classification takes place, where the model determines whether the sign belongs to a certain letter of the alphabet. Finally, the recognition results are interpreted into a suitable symbol associated with the gesture. During the research process, the signs of the dactyl alphabet and interaction features of people with auditory impairment were studied and a dataset of more than 25000 trained data was also created. A model was developed and trained based on the most appropriate architecture for the task of the work. The model was tested and optimized to improve its accuracy. The results of this work can be used in the creation of devices to compensate for poor hearing, providing people with hearing impairment comfort in society.

Keywords: computer vision, sign recognition, dactyl classification, transfer learning, Russian dactyl alphabet, deep learning, computerization, software, assistive technology, convolutional neural networks

The article discusses a method for taking into account the compression of concrete using standard formulas when calculating using an inverse numerical-analytical method, taking into account the actual rigidity of concrete filled steel tube elements. The inverse numerical-analytical method makes it possible to calculate concrete filled steel tube elements for strength and stability under eccentric compression. Dependencies are presented showing the possibility of taking compression into account at various eccentricities and flexibility.

Keywords: concrete filled steel tube elements, CFST, inverse numerical analytical method, nonlinear deformation model, concrete compression,concrete filled steel tube column, eccentric compression

The construction and substantiation of a finite element model of the capillary tube running-in process, which was obtained by drawing on a fixed mandrel, are considered. The rolling rolls are cylindrical and absolutely rigid. The condition for performing the work is a comparison of the resulting gap between the pipe and the mandrel and the facet formed during deformation. The solid-state model of the process is described by an adaptive grid. Under these conditions, an informative model was obtained, which was used in parametric analysis.

Keywords: drawing with a mandrel, capillary tube, extraction, rolling, model construction, compression selection, pipe size tolerance

The work is aimed at modeling the control system of a slitting machine of a paper machine in order to improve the quality of products and eliminate defects in winding density. The developed automated system implements the functions of controlling the operating modes of the machine, distributing the loads of the bearing shafts, braking the roll and tensioning the paper web.

Keywords: slitting machine, paper machine, automated control system, rewinder, pressure roller, decoiler, reeler, accelerating shaft, deflecting shaft, cutting section

The problem of developing an intelligent automated system for detecting defects in textile materials is considered. An analysis of machine learning and deep learning algorithms was carried out in relation to solving the problem of product quality control. The implementation of an artificial neural network implemented in a Raspberry Pi microcomputer and receiving a set of input data in the form of a large stream of images from a high-speed digital camera is considered. The stages of creating a model in Python using the TensorFlow and Keras libraries are described. The development process includes the preparation of initial data intended for training and testing the system, as well as testing the operation of the resulting neural network, which consists in recognizing images of defects on fabric according to classification criteria.

Keywords: machine learning, neural network, defect images, textile material, training, testing, accuracy