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Experimental setups of a two-channel wavefront sensor (WFS) based on moiré deflectometry have been proposed and developed in recent years. The capabilities of this WFS have been tested in the atmospheric turbulence measurements. Like other WFSs, it can be used in various areas. Therefore, we have developed a MATLAB graphical user interface program to allow any user to easily make use it. This program takes simultaneous horizontal and vertical moiré patterns as input data and reconstructs the corresponding wavefront map and its aberration values. The algorithm of the process is explained step by step in this paper. For a typical input moiré pattern, the results such as the wavefront shape and corresponding first ten Zernike coefficients are calculated and are shown as outputs of the software. In addition, there is a special part in the program for atmospheric turbulence applications that calculates the strength amount of the turbulence, C_n² and the temporal evolution of the angle of arrival.

The goal is to study the possibility of creating intelligent automated systems for differential diagnosis of pulmonary diseases based on the identification of pathological structures in X-ray images of thoracic cavity organs using neural network technologies. A brief analysis of modern diagnostic techniques is presented, and a description of the proposed algorithm for determining the type of lung tissue pathologies used in the visual analysis of X-ray images and based on the identification of the main radiological syndromes, as well as on the evaluation of the quantitative characteristics of differential X-ray diagnostics, is given. By the example of classification of radiographs of healthy and tuberculosis patients, the effectiveness of using neural network technologies in the computer diagnosis of lung diseases is demonstrated. The studies are carried out using a publicly available database of X-ray images of thoracic cavity organs containing 3,500 images of healthy people and the same number of sick people images.

The neural network technology is used to accurately calculate the number of wheat ears from photographs of a wheat field. The methods of deep learning of convolutional neural networks in interaction with the transfer learning methodology are used. With the help of the EfficientDet architecture, the neural network is trained, which allows the number of wheat ears to be determined from graphical images with accuracy of 0.88012 on a sample using the F1-score metric with a threshold value of 0.6 (the coincidence of the predicted markup and the actual one).

The possibility of creating a fast-response framing hyperspectrometer functioning as a conventional camera is studied. It is considered how much the classification accuracy will have to be sacrificed for the implementation of the idea of creating a compact and easy-to-use hyperspectral camera with rapidly tunable parameters. Experimental studies of the classification accuracy depending on the number and method of selection of spectral channels, spatial resolution, and bit depth of quantization of the signal brightness are carried out on a test hyperspectral image. It is shown that, though the resulting accuracy decreases, it still remains acceptable for a wide range of practical tasks.

A method of determining the type of objects under observation based on identification of the photometric portrait of the object with one of those available in the database of the current and reference photometric portraits of objects is considered. The proposed approach allows known typical objects to be identified regardless of availability of a priori information about them.

Functionally defined objects for realistic scenes are proposed. Physically correct visualization of three-dimensional objects based on perturbation functions is described. That is, the rendering of materials takes into account the laws of physics. Physically correct reflection models are necessary to obtain photorealistic images. The roughness, micro relief, and surface gloss indicate how smooth or rough the surface of the material is. This paper shows the effects of diffraction taking into account the surface roughness. Subsurface light transport is also considered, which is modeled using bidirectional surface scattering.

The characteristics of a fiber electro-optical intensity modulator in the mode of conversion of microwave signals are investigated. The optimal conditions for efficient generation of the difference frequency of mixed signals at the modulator output are determined.

The features of imaging faces of extended (in depth) slit holes of constant thickness d of symmetrical type (with equal input and output apertures D) with absolutely absorbing internal faces are investigated. The calculations are based on an optical-physical model of diffraction phenomena on extended absolutely absorbing objects using equivalent slit-type transparencies. The structures of images of such objects formed in ideal and diffraction-limited systems are studied. It is shown that the image profiles of the front and back faces of the extended slit hole largely depend on a parameter N_θ0 equal to the ratio of the critical diffraction angle θ_cr = √ λ/d to the half angular size θ₀ of the aperture filter, as well as on the ratio of the slit aperture D to the size of the Fresnel zone δ_d = √ λd. It is shown that, when N_θ0 >> 1, there is a displacement of the object boundaries, which is determined both by the interaction of diffraction pictures of two edges for the case of a flat slit (d = 0) and by the influence of secondary diffraction of light on the back face of the extended object. At D >> √λd, the boundaries are found to be mainly shifted due to secondary diffraction of light, which leads to a systematic error of measuring the aperture D equal to εd = 0,22 δ_d . The features of the formation of diffraction-limited images of the back face with strong volumetric effects (N_θ0 << 1) are investigated.

He article deals with the poorly studied topic of scientific typologization of Indian mathematicians’ research lines, as well as the factor of their personality in mathematical science. This study pays special attention to the suprarational ( superrational , or pararational ) aspect of Indian mathematicians’ personalities, since their religious ideas and philosophical intuitions were obviously not only the most important components of their characters, but also often directed their research. The pre-systemic and systemic periods and the period of personalities of Indian mathematics are considered. Already the first great representatives of Indian mathematics (Aryabhata, Varahamihira and Brahmagupta) realized the principle of suprarationality and each of them formed a whole trend in the historic advancement of mathematics in India - from the free coexistence of science and religion to their synthesis and then to their opposition.

The article notes, considers and assesses the presence of a materialistic component in the philosophy of R. Descartes, which is embodied mainly in the recognition of the independent ontological status of the material world. This is its status as an independent substance. However, Descartes combines this with the assertion of the absolute dependence of everything that exists on the creative activity of the incorporeal god. But even when such dependence is claimed, the existence of something that is present in the corporeal world independently of god is also recognized. Special attention is given to how this parallel adherence to mutually exclusive positions influenced Descartes in advancing the materialistic position as one of them.