The article analyzes the various models used to assess the environmental impact of transport on the ecosystem of cities, developed a software product for automating the methodology for calculating emissions from road transport based on those developed at the Belarusian National Technical University using GPS tracks. Some results of the application of the methodology for assessing environmental losses in road traffic in cities are given with the application to the geomap of a specific section of the road network. Recommendations are given for further improvement of the proposed methodology for assessing environmental losses from transport in the city’s ecosystem.

The regularities of changes in the frequencies and forms of natural oscillations and the stress state of a silicon sensing element of a mechanical MEMS accelerometer system depending on changes in the radii of rounding of structural elements are considered. An increase in the natural frequencies of the system and stresses in torsion suspensions has been established with an increase in the radii of the coupling of the suspension with the frame and the inertial mass. The rounding of the shape of the suspensions in the plan leads to a decrease in natural frequencies and an increase in stresses arising from oscillatory movements. The fact of localization of high-frequency oscillation forms in the inertial mass is confirmed. A set of design solutions is recommended to control the vibration state of the MEMS accelerometer mechanical system.

The article is devoted to the formulation of the problem of synthesis of the control system of an unmanned aerial vehicle (UAV) with the participation of a human operator. An analysis is made of various approaches to the synthesis of systems, models of a human operator as a link in a tracking system, mathematical models and information support for complex human-machine systems, competencies required by UAV operators. The system considers a human operator as a dynamic link that performs compensatory monitoring of the relevant information that is presented on the monitor of the corresponding operator controlling the UAV or its target load in accordance with the task. On the basis of the analysis, a generalized scheme of the UAV control system and its target load is substantiated, a mathematical model of a human operator is studied in the form of a transfer function consisting of five elementary links that take into account the dynamic characteristics of the central nervous system, the delay of the neuromuscular system, the ability of the human operator to smooth random fluctuations of the information presented on the monitor screen received from the telemetry system. As a typical example of a human-machine control system, the ground control point of the multifunctional unmanned aerial complex “Busel” is considered, which includes two workplaces for the UAV control operator and the target load control operator, which is considered equipment designed to monitor objects located on the earth’s surface

To identify and classify objects on images obtained using UAV imaging and orbital-based imaging, a neural network classification model based on the use of an autoencoder and built on the architecture of an ensemble of multilayer perceptrons is proposed. Additionally, at the stage of highlighting informative features, is added a color information, which is based on the per-channel histograms and is invariant to the scale and rotations of the image. The model is implemented using the Keras library. The use of the proposed model for classification into four classes: “Fire”, “Smoke”, “Vegetation” and “Buildings”, allows to achieve a classification accuracy above 99%.  

The traditional tomography is an effective remedy for medical diagnostics, nondestructive control of industrial designs and for quality check of industrial products. Tomographic visualization of objects in case of an incomplete viewing angle, limited number of projections and/or the insufficient power of a source of x-ray radiation is strongly incorrect return task. Article is devoted to case research when noise in input data significantly affect convergence and quality of the reconstructed image.

The article presents results of our experiments carried out to study the invariance of the digital description of the image of a handwritten signature presented on paper. The description is built on the basis of a normalized image of the signature, digitized in the visible range of the electromagnetic spectrum by a scanner, with subsequent calculation of the distribution of its local features. The variability of this representation of the signature under different conditions simulating a change in its color, orientation on paper, line thickness and dimensions has been experimentally studied. It is shown that the digital description of the handwritten signature image, previously proposed by the authors, is sufficiently invariant with respect to the listed conditions for its execution to perform the off-line signature verification procedure.

The article describes the scientific problem of processing images obtained in the infrared range. Methods for filtering such images in order to reduce noise are presented. Methods for optimal smoothing are described. A software tool has been developed that allows you to select the desired objects on the processed images.

The document categorization problem in the case of a large business document flow is considered. Textual and visual embeddings were employed for classification. Textual embeddings were extracted via OCR Tesseract. The Viola and Jones method was applied to generate visual embeddings. This paper describes the performance optimization technology for the implemented classification algorithm. Servers with Intel CPUs were used for the algorithm execution. For single-threaded implementation, high-level and low-level optimizations were performed. High-level optimization was based on the parametrization of the recognition algorithms and the employment of intermediate data. Low-level optimization was carried out via compiler tools allowing for an extended set of SIMD instructions. The implementation of parallelization with several multithreaded applications on multiple servers was also described. The proposed solution was tested using own test data sets of business documents. The proposed method can be applied in modern information systems to analyze the content of a large flow of digital document images.

The paper considers the application of an algorithm based on a morphological projector for determining structural differences for comparing dermoscopic images. This will allow to identify changes that have occurred in skin lesions over time, for a more accurate diagnosis of their malignancy. The proposed algorithm makes it possible to detect differences in images even if there is a significant difference in the brightness and color levels of the compared images, and also ignores small insignificant details, such as noise, dermatoscope optics marks, hair, etc. A method for correcting the desynchronization of images using the structural similarity index as a similarity metric, and the sinecosine algorithm as an optimization algorithm is proposed. The proposed algorithms were tested on dermatoscopic images and the possibility of their application was demonstrated.