<p><span lang="EN-US">An important feature of image analysis is texture, seen in all images, from aerial and satellite images to microscopic images in biomedical research. A chest X-ray is the most common and effective method for diagnosing severe lung diseases such as cancer, pneumonia, and tuberculosis. The lungs are the largest X-ray object. The correct separation of the shapes and sizes of the contours of the lungs is an important reason for diagnosis, because of which an intelligent information environment can be created. Despite the use of X-rays, to identify the diagnosis, there is a chance that the disease will not be detected. In this sense, there is a risk of development, which may be fatal. The article deals with the problems of pneumonia clustering using the autocorrelation function to obtain the most accurate result. This provides a reliable tool for diagnosing lung radiographs. Image pre-processing and data shaping play an important role in revealing a well-functioning basis of the nervous system. Therefore, images from two classes were selected for the task: healthy and with pneumonia. This paper demonstrates the applicability of the autocorrelation function for highlighting interest in lung radiographs based on the fineness of textural features and k-means extraction.</span></p>

This paper discusses some modes of signal transmission for corporate systems using the technology of virtual private networks VPN. A very important property of tunnels is the ability to differentiate different types of traffic and assign them the necessary service priorities. In this work, research has been carried out and comparative characteristics of signal transmission modes using virtual networks have been obtained to identify the effectiveness of the network in various modes of organizing a virtual network, and to optimize a virtual network in order to identify an effective method for organizing a VPN. Also, the work analyzes the specifics of the work of corporate information systems and networks intended for their maintenance, showed that for building a corporate network it is advisable to use virtual private network (VPN) technology, which makes it possible to ensure the fulfillment of the basic requirements for the security and quality of customer service and applications and the current state and direction of development of VPN technology when creating new generation corporate networks, while highlighting the main tasks that need to be addressed when creating a network. Some features of setting up an IPSec VPN server for corporate networks are considered.

The paper is devoted to machine learning methods that focus on texture-type image enhancements, namely the improvement of objects in images. The aim of the study is to develop algorithms for improving images and to determine the accuracy of the considered models for improving a given type of images. Although currently used digital imaging systems usually provide high-quality images, external factors or even system limitations can cause images in many areas of science to be of low quality and resolution. Therefore, threshold values for image processing in a certain field of science are considered. The first step in image processing is image enhancement. The issues of signal image processing remain in the focus of attention of various specialists. Currently, along with the development of information technology, the automatic improvement of images used in any field of science is one of the urgent problems. Images were analyzed as objects: state license plates of cars, faces, sections of the field on satellite images. In this work, we propose to use the models of Super-Resolution Generative Adversarial Network (SRGAN), Extended Super-Resolution Generative Adversarial Networks (ERSGAN). For this, an experiment was conducted, the purpose of which was to retrain the trained ESRGAN model with three different architectures of the convolutional neural network, i.e. VGG19, MobileNet2V, ResNet152V2 to add perceptual loss (by pixels), also add more sharpness to the prediction of the test image, and compare the performance of each retrained model. As a result of the study, the use of convolutional neural networks to improve the image showed high accuracy, that is, on average ESRGAN+MobileNETV2 – 91 %, ESRGAN+VGG19 – 86 %, ESRGAN+ResNet152V2 – 96 %.

Under electromagnetic impact (EMI) of a sufficient level, temporary disruption of functioning, processing, transmission and storage of information in cellular equipment is possible. Possible problems of electromagnetic compatibility (EMC) of a mobile phone and a base station (BS) of cellular connection under the influence of electromagnetic radiation (EMR) from other sources and their negative impact on functioning are considered. The energy of the HF electromagnetic field (EMF) after passing through the protective case can affect the devices of shielded radio electronic equipment (REE), therefore, the possible negative consequences of the impact of high-energy EMF on the REE are described. Possible negative consequences under certain conditions from the influence of the skin-effect, the effects of electrostatic discharge and electromagnetic pulses on electronic devices are given. It is shown that the constructional method of protecting REE from the effects of external electromagnetic factors consists in reducing the collected and transmitted EMF energy by improving the design, placement and installation of equipment. Components of some vendors for 5G systems that are resistant to external interference are given, and the possibilities for reducing the radiation level of a cell phone are noted. The necessity of an integrated approach to solving EMC problems is substantiated, which consists in the use of structural, circuitry and structural-functional methods of EMC provision. The new 5G (Fifth Generation) standard will operate at higher operating frequencies compared to previous generations. Due to the workload of the electromagnetic spectrum at frequencies below 6 GHz, 5G networks will be based on wireless radio access systems operating at frequencies of 30–100 GHz, that is, in the lower band of the extremely high frequency range EHF (Extremely High Frequency), 30–300 GHz.