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The widespread use of risograph printing in printing houses requires an increase in the speed of equipment while maintaining the printing quality of the original layouts. The problem of risograph printing is not always obtaining high-quality images, since the risographs used in the standard driver (periodic, non-periodic) do not always allow you to get the printed image the same as in the original. This is reflected in the insufficiency of parameters such as image clarity and sharpness. Problems of poor quality of risograph printing can be solved by changing the settings of the risograph driver for the original layout with additional use of digital filtering and image rasterization. This will require the creation of additional image rasterization methods to improve the initial indicators of the original layout in contrast, clarity, and the correctness of the transmission of halftone images and will improve the quality of printed images, as well as ensure the efficiency of the printing process for a wide range of original layouts.

Creation of new digital technologies let automate the reproduction of text and graphic information, led to the creation and development of the digital printing. Digital printing is a technology for producing prints in the printer based on the original layout, created as corresponding codes with a computer. One of the technologies of digital printing is a computer-to-press and one of the devices in this direction is risograph. The risograph printing quality is worse than offset printing. The text is printing with medium sharpness and images remind photos in old newspapers and require special preparation. But risograph is the most profitable solution for small and medium circulations from 50 up to 1000 sheets. Wide usage of risograph printing in typographies demands increase performance of the equipment with the high print quality of digital images. To improve the quality of risographic printing, the creation of methods is required to form the initial indicators of the original layout (clarity, correct transmission of halftones, contrast). At the same time, the result of obtaining high-quality images obtained by printing on a risograph is affected by surface microgeometry and the physical and mechanical properties of paper. So, the optical density of the ink layer on the print is largely determined by the structure of the sections of paper, in particular, absorbency and porosity. To obtain high-quality images on prints, it is necessary not only to customize the original layout, but also to select paper with such characteristics that would allow you to get the best result when printing on a risograph. Since the risograph occupies an intermediate place in quality between copying equipment and laser printing, a laser print is taken as the standard for print quality. And one of the tasks of the quality of risographic prints is to increase it to the quality of laser printing.

In real-world networks, many problems imply finding the All-Pairs Shortest Paths (APSP) and their distances in a graph. Solving the large-scale APSP problem on modern multi-processor (multi-core) systems is the key for various application domains. The computational cost of solving the problem is high, therefore in many cases approximate solutions are considered as acceptable. The blocked APSP algorithms are a promising approach which can exploit many processors (cores) and their caches in parallel mode efficiently. At the same time, to our best knowledge, all blocked algorithms of the Floyd-Warshall family use blocks of equal sizes. This property limits application of the algorithms. In this paper we propose new blocked algorithms which divide the input graph into unequal subgraphs and divide the matrix of distances between pairs of vertices into blocks of unequal sizes. The algorithms describe the dense subgraphs by the adjacency matrix and describe sparse subgraphs and connections between them by the adjacency list. This approach allows the Floyd-Warshall family algorithms to be used together with Dijkstra family algorithms. It can be applied to large graphs decomposed into dense (clusters) and sparse subgraphs. A new heterogeneous algorithm can significantly reduce the computation time of blocks depending on the block type and size. The contribution of the paper is the development of a new family of blocked APSP algorithms which can handle blocks of unequal sizes, save and extend the advantages of the state-of-the-art algorithms operating on blocks of equal sizes. The proposed algorithms are implemented as single- and multiple-threaded parallel applications for multi-core systems.

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 allocation of experts to programmer teams, which meet constraints on professional competences related to programming technologies, languages and tools an IT project specifies is a hard combinatorial problem. This paper solves the problem of forming the maximum number of teams whose experts meet all the constraints within each team. It develops and compares two algorithms: a heuristic greedy and exact optimal. The greedy algorithm iteratively solves the set cover problem on a matrix of expert competences until can create the next workable team of remaining experts. The paper proves that the allocation greedy algorithm is not accurate even if the set cover algorithm is exact. We call the allocation algorithm as double greedy if the set cover algorithm is greedy. The exact algorithm we propose finds optimal solution in three steps: generating a set of all non-redundant teams, producing a graph of team’s independency, and searching for a maximum clique in the graph. The algorithm of generating the non-redundant teams traverses a search tree constructed in such a way as to guarantee the creation of all non-redundant teams and absorbing all redundant teams. The edges of the non-redundant team independency graph connect teams that have no common expert. The maximum clique search algorithm we propose accounts for the problem and graph features. Experimental results show that the exact algorithm is a reference one, and the double-greedy algorithm is very fast and can yield suboptimal solutions for large-size allocation problems.

Block symmetric ciphers are one of the most important components of modern information security systems. At the same time, in addition to the structure of the applied block symmetric cipher, the cryptographic strength and performance of the information protection system is largely determined by the applied encryption mode. In addition to high performance and high-quality destruction of block statistics, modern encryption modes should also protect encrypted information from occurred or intentionally introduced errors. In this paper, we have developed an encryption mode with blocks skipping and using a pseudo-random key sequence generator, which allows checking the integrity of encrypted information with accurate detection of the place where an error was introduced. In this case, the error detection accuracy is determined by the adjustable parameter of the macroblock size and can be set depending on the level of importance of the protected information. The developed encryption mode is characterized by the following key advantages: reducing the number of required encryption operations by half, while providing a high level of cryptographic quality; more effective destruction of macroblock statistics due to the use of an additional generator of pseudo-random key sequences, the impossibility of propagation of the occurred (intentionally introduced) error outside the macroblock, as well as higher values of the number of protection levels due to the possibility of classifying the initial states of the applied generators of pseudo-random key sequences. As proposed in this paper, the mode of authenticated encryption with blocks skipping can be recommended for use on mobile platforms that are demanding both in terms of the quality and reliability of the protected information and are limited in terms of computing and power resources.

This paper is devoted to the reduction of data transfer between the main memory and direct mapped cache for blocked shortest paths algorithms (BSPA), which represent data by a D[M×M] matrix of blocks. For large graphs, the cache size S = δ×M2, δ < 1 is smaller than the matrix size. The cache assigns a group of main memory blocks to a single cache block. BSPA performs multiple recalculations of a block over one or two other blocks and may access up to three blocks simultaneously. If the blocks are assigned to the same cache block, conflicts occur among the blocks, which imply active transfer of data between memory levels. The distribution of blocks on groups and the block conflict count strongly depends on the allocation and ordering of the matrix blocks in main memory. To solve the problem of optimal block allocation, the paper introduces a block conflict weighted graph and recognizes two cases of block mapping: non-conflict and minimum-conflict. In first case, it formulates an equitable color-class-size constrained coloring problem on the conflict graph and solves it by developing deterministic and random algorithms. In second case, the paper formulates a problem of weighted defective color-count constrained coloring of the conflict graph and solves it by developing a random algorithm. Experimental results show that the equitable random algorithm provides an upper bound of the cache size that is very close to the lower bound estimated over the size of a complete subgraph, and show that a non-conflict matrix allocation is possible at δ = 0.5 for M = 4 and at δ = 0.1 for M = 20. For a low cache size, the weighted defective algorithm gives the number of remaining conflicts that is up to 8.8 times less than the original BSPA gives. The proposed model and algorithms are applicable to set-associative cache as well.

The paper discusses the key factors and trends in the design and production of printed circuit boards (PCB), which determine the state of the art of the automatic PCB inspection. To search for and classify defects, it is proposed to use the method of detecting defects in images based on the YOLO family of object detection models. The model was trained on a public set of images of PCB with 6 classes of defects, and the accuracy was assessed using generally accepted metrics. On the test dataset, the average accuracy according to the mAP50 metric is 0.98.

The problem of finding all shortest paths between vertices in a graph (APSP) has real-life applications in planning, communication, economics and many other areas. APSP problem can be solved using various algorithms, starting from Floyd-Warshall’s algorithm and ending with advanced, much faster blocked algorithms like Heterogeneous Blocked All-Pairs Shortest Path Algorithm designed to fully utilize underlying hardware resources and utilize inter-data relationships. In the paper, we propose a novel Blocked all-pairs Shortest Paths algorithm for Clustered Graphs (BSPCG) (in sequential and parallel forms) which utilizes the graph clustering information to significantly reduce the number of calculations by performing shortest paths search only though bridge vertices between clusters. We performed a set of comparing experiments for BSPCG and standard Blocked All-Pairs Shortest Path (BFW) algorithm on four randomly generated graphs of 4800 and 9600 vertices with different cluster configurations to determine the efficiency of calculation of paths passing through bridge vertices. All experiments were executed on a computer with two Intel Xeon E5-2620v4 processors (8 cores, 16 hardware threads and shared 20 MB L3 cache). In all the experiments the novel BSPCG algorithm outperformed the standard BFW algorithm. In single-threaded scenarios, BSPCG outperformed BFW up to 4.6 times on graphs of 4800 vertices and up to 2.7 times on graphs of 9600 vertices. In the multi-threaded scenarios, BSPCG also outperformed BFW up to times on graphs of 4800 vertices and up to 2.7 times on graphs of 9600 vertices. The proposed algorithm can be used in scenarios where clustering information stays intact or slightly modified based on the changes in graph and can be reused for future calculation of all-pairs shortest paths in the graph.

In this paper, we propose to use a discrete wavelet transform with a singular wavelet to isolate the periodic component from the signal. Traditionally, it is assumed that the validity condition must be met for a basic wavelet (the average value of the wavelet is zero). For singular wavelets, the validity condition is not met. As a singular wavelet, you can use the Delta-shaped functions, which are involved in the estimates of Parzen-Rosenblatt, Nadaraya-Watson. Using singular value of a wavelet is determined by the discrete wavelet transform. This transformation was studied earlier for the continuous case. Theoretical estimates of the convergence rate of the sum of wavelet transformations were obtained; various variants were proposed and a theoretical justification was given for the use of the singular wavelet method; sufficient conditions for uniform convergence of the sum of wavelet transformations were formulated. It is shown that the wavelet transform can be used to solve the problem of nonparametric approximation of the function. Singular wavelet decomposition is a new method and there are currently no examples of its application to solving applied problems. This paper analyzes the possibilities of the singular wavelet method. It is assumed that in some cases a slow and fast component can be distinguished from the signal, and this hypothesis is confirmed by the numerical solution of the real problem. A similar analysis is performed using a parametric regression equation, which allows you to select the periodic component of the signal. Comparison of the calculation results confirms that nonparametric approximation based on singular wavelets and the application of parametric regression can lead to similar results.

Addition is one of the timing critical operations in most of modern processing units. For decades, extensive research has been done devoted to designing higher speed and less complex adder architectures, and to developing advanced adder implementation technologies. Decision diagrams are a promising approach to the efficient many-bit adder design. Since traditional binary decision diagrams does not match perfectly with the task of modelling adder architectures, other types of diagram were proposed. If-decision diagrams provide a parallel many-bit adder model with the time complexity of Ο(log2n) and area complexity of Ο(n×log2n). The paper propose a technique, which produces adder diagrams with such properties by systematically cutting the diagram’s longest paths. The if-diagram based adders are competitive to the known efficient Brent-Kung adder and its numerous modifications. We propose a blocked structure of the parallel if-diagram-based adders, and introduce an adder table representation, which is capable of systematic producing if-diagram of any bit-width. The representation supports an efficient mapping of the adder diagrams to VHDL-modules at structural and dataflow levels. The paper also shows how to perform the adder space exploration depending on the circuit fan-out. FPGA-based synthesis results and case-study comparisons of the if-diagram-based adders to the Brent-Kung and majority-invertor gate adders show that the new adder architecture leads to faster and smaller digital circuits.

The work discusses a number of techniques for segmenting dermoscopic images of skin lesions to identify the areas occupied by these lesions. Segmentation is necessary as the first stage of most methods of computer diagnostics of malignancy of neoplasms. A number of techniques, such as ABCDE, use the shape of the tumor as one of the criteria for making a diagnosis; for others, such as the use of convolutional neural networks, identifying the tumor allows one to increase the accuracy of the results obtained. The work discusses three methods of segmentation: thresholding using Otsu's method to calculate the threshold value, a convolutional neural network built on the U-net architecture, and a similar convolutional neural network with an added attention mechanism. The advantages and disadvantages of each method are considered, as well as the possibility of using them together to obtain the best segmentation results.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 sine-cosine algorithm as an optimization algorithm is proposed. The proposed algorithms were tested on dermatoscopic images and the possibility of their application was demonstrated.

The problem of calculating a quantitative quality assessment of digital images of metal object fractures recorded by a camera or a digital microscope is considered. Quality assessment is performed when the reference images are absent. The paper presents an approach based on calculation of local estimates followed by analysis of their distribution. Several variants for calculation of local estimates have been studied. Those whose distribution is unimodal were selected. It is shown that the average of local estimates is an acceptable general characteristic of image quality if they have a normal (Gaussian) distribution. In this case, the average is one of its parameters. Otherwise, the parameters of the Weibull distribution can serve as more accurate quantitative characteristics of image quality in general. The proposed approach divides more objectively the set of the analyzed images into two groups those with satisfactory or unsatisfactory quality for performing expert studies using images. Examples of the quality assessment of different object images recorded at different resolutions are presented.

The problem of approximation is relevant for most engineering applications. In this connection, the universal methods of approximation are of interest. The method of nonparametric approximation is developing in the paper – the method of singular wavelets. The method includes an effective numerical algorithm based on the summation of a recursive sequence of functions. The universal algorithm of approximation makes it possible to apply it to approximate one-dimensional and multidimensional functions, in decision support systems, in the processing of stochastic information, pattern recognition, and solution of boundary-value problems.The introduction explain the idea of the method of singular wavelets – to combine the theory of wavelets with the Nadaraya-Watson kernel regression estimator. Usually, Nadaraya-Watson kernel regression are considered as an example of non- parametric estimation. However, one parameter, the smoothing parameter, is still present in the traditional kernel regression algorithm. The choice of the optimal value of this parameter is a complex mathematical problem, and numerous studies have been devoted to this question. In the approximation by the method of singular wavelets, summation of Nadaraya-Watson kernel regression estimates with the smoothing parameter takes place, which solves the problem of the optimal choice of this parameter.In the main part of the paper theorems are formulated that determine the properties of the regularized wavelet transform. Sufficient conditions for uniform convergence of the wavelet series are obtained for the first time. To illustrate the effectiveness of the numerical approximation algorithm, we consider an example of the quasi-interpolation of the Runge function by wavelets with a uniform distribution of interpolation nodes.

In recent decades, perfect algebraic constructions are successfully being use to signal systems synthesis, to construct block and stream cryptographic algorithms, to create pseudo-random sequence generators as well as in many other fields of science and technology. Among perfect algebraic constructions a significant place is occupied by bent-sequences and the class of perfect binary arrays associated with them. Bent-sequences are used for development of modern cryptographic primitives, as well as for constructing constant amplitude codes (C-codes) used in code division multiple access technology. In turn, perfect binary arrays are used for constructing correction codes, systems of biphase phase- shifted signals and multi-level cryptographic systems. The development of methods of many-valued logic in modern information and communication systems has attracted the attention of researchers to the improvement of methods for synthesizing many-valued bent-sequences for cryptography and information transmission tasks. The new results obtained in the field of the synthesis of ternary bent-sequences, make actual the problem of researching the class of perfect ternary arrays. In this paper we consider the problem of extending the definition of perfect binary arrays to three-valued logic case, as a result of which the definition of a perfect ternary array was introduced on the basis of the determination of the unbalance of the ternary function. A complete class of perfect ternary arrays of the third order is obtained by a regular method, bypassing the search. Thus, it is established that the class of perfect ternary arrays is a union of four subclasses, in each of which the corresponding methods of reproduction are determined. The paper establishes the relationship between the class of ternary bent-sequences and the class of perfect ternary arrays. The obtained results are the basis for the introduction of perfect ternary arrays into modern cryptographic and telecommunication algorithms.

Security In the paper some aspects of visible light pulses using for hidden information transmitting are considered. We have investigated perception of the human vision to visual light pulses which have different power and frequency. It is established that pulsed light source becomes invisible at certain ratio of radiating light stream and ambient light level (background lighting (BL)). For example, in the case of background lighting E = 400 lx light pulses following with frequency 50 Hz are invisible when their power is less than 0.12 W. In the paper we represented experimental frequency dependence of the power of light pulses which are invisible for human eye at BL preset level.To eliminate the influence of distracting and masking factors (for example, BL pulsations) we offer to choose LED matrixes powered by stabilized adjustable DC power supply unit as an optimal BL source. Based on experimental data about current and temperature dependences of light stream power and LED matrix radiation spectra we developed a method of assignment of BL level by changing LED current. Approximating equation for dependence of light stream quantity versus LED current in the case of thermostatting is obtained. Temperature self-regulation effect of the heater, which has positive temperature coefficient of resistance, can satisfactorily solve the problem of temperature stabilization of LED background lighting source. In the case of thermostat heater made from material with positive temperature coefficient of resistance 0.48 K-1 the change of LED matrix temperature was 7 times less than without thermostat.To provide research in wide frequency and duration ranges of pulse sequences (10–3–103 Hz and 10–7–1 s) a pulse generator was developed and made using microcontroller PIC18F2550.

The classification of methods for land surface image segmentation is presented in the paper. Such approaches as template matching, machine learning and deep neural networks, as well as application of knowledge about analyzed objects are considered. Peculiarities of vegetation indices application for satellite images data segmentation are considered. Advantages and disadvantages are noted. The results obtained by the authors of the methods that have appeared over the last 10 years are systematized, which will allow those interested to get oriented faster and form ideas for further research.

The solar energy is directly converted into electrical energy by solar PV module. Each type of PV module has its own specific characteristic corresponding to the surrounding condition such as irradiation, and temperature and this makes the tracking of maximum power point (MPP) a complicated problem. To overcome this problem, many maximum power point tracking (MPPT) control algorithms have been presented. Fuzzy logic (FL) has been used for tracking the MPP of PV modules because it has the advantages of being robust, relatively simple to design and does not require the knowledge of an exact model where a mathematical model of the PV module, DC-DC converter, are used in the study of FL based MPPT algorithm. It is suggested to present this problem in the form of two-folds; first to identify the deviation of the power to maximum power point, and secondly, to control the voltage of the DC-DC converter corresponding to maximum power. In this paper, the first discussion approach will stress out the integration of model predictive control in maximum power point tracking MPPT and as progressing a second approach is identified as fuzzy logic controller FLC and perturb & Observe P&O algorithms are analyzed. All are interrelated to MPPT model for a photovoltaic module, PVM, to search for and generate the maximum power; in this case what’s called P-max. As per the first technique the focus is on the optimal duty ratio, D, for a series of multi diverse types of converters and load matching. The design of the MPPT for a stand-alone photovoltaic power generation system is applied where the system will consist of a solar array with nonlinear time varying characteristics, and a converter with appropriate filters. The integration of model predictive control will be addressed first in this paper. The second fold will implement an MPPT system that use the FLC and compare it with a classical MPPT P&O algorithm through the utilization of Simulink. The novel design in the FLC will be based on the use of asymmetrical membership functions to compensate for the asymmetrical P-V curve of solar panel.

Practical application of advanced algebraic constructions in modern communication systems based on MC-CDMA (Multi Code Code Division Multiple Access) technology and in cryptography necessitates their further research. One of the most commonly used advanced algebraic construction is the binary bent-function having a uniform amplitude spectrum of the Walsh-Hadamard transform and, accordingly, having the maximal distance from the codewords of affine code. In addition to the binary bent-functions researchers are currently focuses on the development of synthesis methods of their many-valued analogues. In particular, one of the most effective methods for the synthesis of many-valued bent-functions is the method based on the Agievich bent-squares. In this paper, we developed a regular synthesis method of the ternary bent-squares on the basis of an arbitrary spectral vector and the regular operator of the triad shift. The classification of spectral vectors of lengths N = 3 and N = 9 is performed. On the basis of spectral classification more precise definition of many-valued bent-sequences is given, taking into account the existence of the phenomenon of many-valued bent-sequences for the length, determined by odd power of base. The paper results are valuable for practical use: the development of new constant amplitude codes for MC-CDMA technology, cryptographic primitives, data compression algorithms, signal structures, algorithms of block and stream encryption, based on advanced principles of many-valued logic. The developed bent-squares design method is also a basis for further theoretical research: development of methods of the permutation of rows and columns of basic bent-squares and their sign coding, synthesis of composite bent-squares. In addition, the data on the spectral classification of vectors give the task of constructing the synthesis methods of bent-functions of lengths N = 32k+1, k Є ℕ.

This paper introduces the design and development of QMRS (Quadcopter Mobile Robotic System). QMRS is a real-time obstacle avoidance capability in Belarus-132N mobile robot with the cooperation of quadcopter Phantom-4. The function of QMRS consists of GPS used by Mobile Robot and image vision and image processing system from both robot and quad-copter and by using effective searching algorithm embedded inside the robot. Having the capacity to navigate accurately is one of the major abilities of a mobile robot to effectively execute a variety of jobs including manipulation, docking, and transportation. To achieve the desired navigation accuracy, mobile robots are typically equipped with on-board sensors to observe persistent features in the environment, to estimate their pose from these observations, and to adjust their motion accordingly. Quadcopter takes off from Mobile Robot, surveys the terrain and transmits the processed Image terrestrial robot. The main objective of research paper is to focus on the full coordination between robot and quadcopter by designing an efficient wireless communication using WIFI. In addition, it identify the method involving the use of vision and image processing system from both robot and quadcopter; analyzing path in real-time and avoiding obstacles based-on the computational algorithm embedded inside the robot. QMRS increases the efficiency and reliability of the whole system especially in robot navigation, image processing and obstacle avoidance due to the help and connection among the different parts of the system.

This paper shows the results of computer modeling of the processes of excitation and propagation of autowaves in distributed active media with inhomogeneous properties. The study of autowaves by the cellular automata method is based on the Wiener–Rosenbluth model, according to which each element of the active environment can be in one of three states: rest, excitation and refractoriness. The software module "AutoWaveModel" has been developed in C++ using the Qt library and OpenGL technology for modeling dynamic processes of excitation of spiral waves and pacemakers. The heterogeneity of the properties of the active environment in the model under consideration is set, in particular, by introducing into the field (volume) of modeling a certain number of inactive elements distributed according to a random law. It is established that the decay of autowaves occurs when about 30-60% of inactive elements are introduced from their total number in the model, moreover, the wave propagation process becomes more stable with an increase in the decay coefficient of the activator of all elements. As one of the factors creating heterogeneity of the active distributed environment, the change in the decay coefficient of the activator in its volume is also considered. In this case, each cell of the model is assigned a random value of the specified coefficient, lying in a given interval from the minimum to the maximum value. With a significant difference in the values of the activator decay coefficient in near areas of the active environment and a sufficiently high excitation threshold, the wave front is curved due to its acceleration or deceleration. In this case, the destruction of the wave is also observed, which is unable to overcome the area with a reduced decay coefficient of the activator.

The paper developed a mathematical model of the control system for a mobile tracked robot, which takes into account the kinematic parameters (angular speeds of rotation of the rollers and the center of mass of the robot, the linear speed of the robot and its angle of rotation relative to the normal to the axis) and dynamic parameters (moments of inertia, resistance forces and electromechanical parameters used electric motors), which made it possible to give the most complete mathematical representation of the description of the movement of a caterpillar mobile robot. A control system for mobile robots along a predetermined trajectory is obtained, taking into account position feedback.

In modern higher education, it is required not only to prepare students to perform work on finished tasks in the subject area they have studied. It is also necessary to prepare students for independent activities, in which students do not work on ready-made tasks, but, on the contrary, are looking for niches in business, in which they themselves can offer in the subject area they have mastered, business-demanded solutions. This is another area of activity, which also requires development while studying at a university. It can be defined as "entrepreneurial competencies of a student." In recent years, the direction "Startup as a Diploma" has been developing, in which a university graduate protects not conditional academic work, but a real technological project with business prospects, to which the students developing it have ownership rights. The creation and maintenance of such projects changes the relationship between student and teacher, for this activity it is necessary to change the traditional teaching methodology. As a task of teachers, we decided to do the following: Find a subject area related to IT development, in which, due to recent achievements, there are opportunities for fast, technically not very complex technological solutions available to students, with the help of which you can create popular solutions. The work proposes an open source software development project, within which students can, performing tasks that are feasible for themselves, create software applications that are in demand in practice, as well as develop development strategies for related business projects. The project is dedicated to solving the problem of determining the coordinates of observed objects and phenomena based on data entered simultaneously by several users in different places using household mobile devices without using special technological equipment such as theodolites or tacheometers. The authors developed a mobile application, the value of which lies in the fact that in the public field allows you to realize the monitoring potential of the population interested in preventing unwanted or dangerous events and preventing emergency situations; professional allows you to assess the quality of the navigation signal in conditions of possible targeted interference; in the educational aspect organize training in the methods of joint fixation of objects and target designation on educational geopolygons. Currently, the project is being developed by students of the Department of Data Analysis and Machine Learning of the Financial University under the Government of the Russian Federation and the Moscow State University of Geodesy and Cartography. This paper presents a description of the project, the proposed solution architecture. References to source code repositories are given. The results of the pilot versions of the software are given.

Modern multi-core processors, operating systems and applied software are being designed towards energy efficiency, which significantly reduces energy consumption. Energy efficiency of software depends on algorithms it implements, and, on the way, it exploits hardware resources. In the paper, we consider sequential and parallel implementations of four algorithms of shortest paths search in dense weighted graphs, measure and analyze their runtime, energy consumption, performance states and operating frequency of the Intel Core i7-10700 8-core processor. Our goal is to find out how each of the algorithms influences the processor energy consumption, how the processor and operating system analyze the workload and take actions to increase or reduce operating frequency and to disable cores, and which algorithms are preferable for exploiting in sequential and parallel modes. The graph extension-based algorithm (GEA) appeared to be the most energy efficient among algorithms implemented sequentially. The classical Floyd-Warshall algorithm (FW) consumed up to twice as much energy, and the blocked homogeneous (BFW) and heterogeneous (HBFW) algorithms consumed up to 52.2 % and 21.2 % more energy than GEA. Parallel implementations of BFW and HBFW are faster by up to 4.41 times and more energy efficient by up to 3.23 times than the parallel implementation of FW and consume less energy by up to 2.22 times than their sequential counterparts. The sequential GEA algorithm consumes less energy than the parallel FW, although it loses FW in runtime. The multi-core processor runs FW with an average frequency of 4235 MHz and runs BFW and HBFW with lower frequency of 4059 MHz and 4035 MHz respectively.

In the paper, a new feature for describing a digital image of a handwritten signature based on the frequency distribution of the values of the local curvature of the signature contours, is proposed. The calculation of this feature on the binary image of a signature is described in detail. A normalized histogram of distributions of local curvature values for 40 bins is formed. The frequency values recorded as a 40-dimensional vector are called the local curvature code of the signature.During verification, the proximity of signature pairs is determined by correlation between curvature codes and LBP codes described by the authors in [23]. To perform the signature verification procedure, a two-dimensional feature space is constructed containing images of the proximity of signature pairs. When verifying a signature with N authentic signatures of the same person, N(N-1)/2 patterns of the proximity of pairs of genuine signatures and N images of pairs of proximity of the analyzed signature with genuine signatures are presented in the feature space. The Support Vector Machine (SVM) is used as a classifier.Experimental studies were carried out on digitized images of genuine and fake signatures from two databases. The accuracy of automatic verification of signatures on the publicly available CEDAR database was 99,77 % and on TUIT was 88,62 %.

This paper extends the recently introduced approach for modeling and solving the optimal control problem of fixedswitched mode DC-DC power converter. DCDC converters are a class of electric power circuits that used extensively in regulated DC power supplies, DC motor drives of different types, in Photovoltaic Station energy conversion and other applications due to its advantageous features in terms of size, weight and reliable performance. The main problem in controlling this type converters is in their hybrid nature as the switched circuit topology entails different modes of operation, each of it with its own associated linear continuous-time dynamics.This paper analyses the modeling and controller synthesis of the fixed-frequency buck DC-DC converter, in which the transistor switch is operated by a pulse sequence with constant frequency. In this case the regulation of the DC component of the output voltage is via the duty cycle. The optimization of the control system is based on the formation of the control signal at the output.It is proposed to solve the problem of optimal control of a hybrid system based on the formation of the control signal at the output of the controller, which minimizes a given functional integral quality, which is regarded as a linear quadratic Letov-Kalman functional. Search method of optimal control depends on the type of mathematical model of control object. In this case, we consider a linear deterministic model of the control system, which is common for the majority of hybrid electrical systems. For this formulation of the optimal control problem of search is a problem of analytical design of optimal controller, which has the analytical solution.As an example of the hybrid system is considered a step-down switching DC-DC converter, which is widely used in various electrical systems: as an uninterruptible power supply, battery charger for electric vehicles, the inverter in solar photovoltaic power plants.. A qualitative change in the projected illustration of the control signal, a sequence of control pulses and output management object (inverter).

In the paper a method of automatical counting the number of cell nuclei in histological images is studied. This operation is commonly used in the diagnostics of various diseases and morphological analysis of cells. In this connection, the procedure of automatical count the number of cell nuclei is a key step in the systems of medical imaging microscopic analysis of histological preparations. The main aim of our work was to develop an efficient scheme of automatic counting cell nuclei based on advanced image processing methods: directional filtering, adaptive image binarization and mathematical morphology. Unlike prior research, the presented approach does not provide segmentation of cell nuclei in the image, but only requires to detect them and count their number. This avoids complex algorithmic calculations and provides good accuracy of counting cell nuclei.The paper describes a series of experiments conducted to assess the effectiveness of the proposed method using the available online database of medical test histological images. Critical parameters defined algorithms, configurable at each stage of image analysis. For each parameter we have defined value ranges, and then realized a selection of optimal values for every parameter and a mutual combination of them. It is based on generally accepted quantitative measures of precision and recall. The results were compared with the state-of-art investigations in this field and demonstrated an acceptable level of accuracy of the proposed method. The software prototype developed during the study can be regarded as an automatic tool for analysis of cell nuclei. The presented approach can be adapted to various problems of analysis of cell nuclei of various organs.

With the spread of diabetes mellitus, diabetic retinopathy (DR) is becoming a major public health problem (especially in developing countries). The long-term complications resulting from DR have a significant impact on patients. Early diagnosis and subsequent treatment can reduce the damage to health. Predictive analytics can be based on the analysis of human retinal images using convolutional neural networks. In this paper, the research focuses on the development of an efficient method for DR detection based on the EfficientNet convolutional neural network, self-learning technology and data augmentation operations. As a result of the experiments, a neural network classifier based on convolutional neural networks is developed, recommendations for data augmentation operations are given. Experiments were performed on the public dataset and showed that it is possible to achieve the proportion of correctly classified objects equal to 97.14 % on the test set from the public dataset.

The article presents results of our experiments carried out to study the invariance of the digital description of the imageThere in the paper is formulated a mathematical problem of multi-hypothetical detection of subclinical and clinical mastitis in dairy cows by the maximum values of udder temperature measured by digital processing of the udder thermal images. The optimal temperature threshold values corresponding to the Bayesian criterion of the minimum average risk in the above multi-hypothesis detection problem are determined by numerical modelling.

The purpose of this paper is to present an alternative maximum power point tracking, MPPT, algorithm for a photovoltaic module, PVM, to produce the maximum power, Pmax, using the optimal duty ratio, D, for different types of converters and load matching.We present a state-based approach to the design of the maximum power point tracker for a stand-alone photovoltaic power generation system. The system under consideration consists of a solar array with nonlinear time-varying characteristics, a step-up converter with appropriate filter.The proposed algorithm has the advantages of maximizing the efficiency of the power utilization, can be integrated to other MPPT algorithms without affecting the PVM performance, is excellent for Real-Time applications and is a robust analytical method, different from the traditional MPPT algorithms which are more based on trial and error, or comparisons between present and past states. The procedure to calculate the optimal duty ratio for a buck, boost and buck-boost converters, to transfer the maximum power from a PVM to a load, is presented in the paper. Additionally, the existence and uniqueness of optimal internal impedance, to transfer the maximum power from a photovoltaic module using load matching, is proved.

The objective of this study is to develop a model rizograficheskoy based printing functions package IPT and automated profile selection rizograficheskoy printing. Work risograph for halftone printing consists of two stages – production of screen form (master film) and printing. The master film is supplied and installed in the printing machine in the form of rolls of different sizes, depending on the print size and model of the device. The capacity of the roll is measured in squares – segments of the printing material. Master-film for risograph consists of three layers: a solid but porous layer such as a paper web neprokleennogo and without fillers; an adhesive layer bonding the paper web to the upper layer; upper, thin polymer layer.

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.

Finding shortest paths in a weighted graph is one of the key problems in computer-science, which has numerous practical applications in multiple domains. This paper analyzes the parallel blocked all-pairs shortest path algorithm at the aim of evaluating the influence of the multi-core system and its hierarchical cache memory on the parameters of algorithm implementation depending on the size of the graph and the size of distance matrix’s block. It proposes a technique of tuning the block-size to the given multi-core system. The technique involves profiling tools in the tuning process and allows the increase of the parallel algorithm throughput. Computational experiments carried out on a rack server equipped with two Intel Xeon E5-2620 v4 processors of 8 cores and 16 hardware threads each have convincingly shown for various graph sizes that the behavior and parameters of the hierarchical cache memory operation don’t depend on the graph size and are determined only by the distance matrix’s block size. To tune the algorithm to the target multi-core system, the preferable block size can be found once for the graph size whose in-memory matrix representation is larger than the size of cache shared among all processor’s cores. Then this blocksize can be reused on graphs of bigger size for efficient solving the all-pairs shortest path problem

This paper presents a technique for obtaining of the main statistical characteristics of the distance estimation between the flying object and a hyperbolic navigation system using two Doppler frequency shifts of the navigation signal. This problem arises when the guidance of the object at a target point along a hyperbola using a bistatic hyperbolic navigation system is considered. Despite the fact that the object guidance loop is closed according to the time difference of arrival information, it is necessary to enter the distance between the object and the center of the navigation system into the algorithm for generating control commands in order to stabilize the frequency response of the control loop and eliminate dynamic errors. This article discusses the statistical characteristics of the estimated range based on the measurements of three values of the object’s speed: its own speed and two projections of this speed on the lines connecting the object with the navigation positions.

The paper describes a method for condition monitoring of a complex mechanical system based on pre-computer FEM simulation of vibrations. The interrelation of vibrations of the connected elements of the system, described by transfer functions, is shown. The occurrence of resonant vibrations in directions orthogonal to the direction of the disturbing effect is revealed. The method for calculating of orthogonal direction vibration amplitudes can be based on measuring the values of the of vibrations in one direction and the regularities of the ratio of the amplitudes of vibrations.

This article is devoted to the development of a method for detecting forgery of handwritten signatures. The signature still remains one of the most common methods of identification. The signature on financial and other documents can be forged, so detecting forgery is an urgent task. This is the task of binary classification: to determine whether the signature is genuine or fake.The article describes the results of recognition of handwritten signatures made on paper. A database of handwritten signatures of 10 people was used for experiments. For each person, 10 genuine and 10 forgery signatures made by other people were collected. The signatures were digitized as color images with a resolution of 850×550 pixels. Then a binary representation of each signature was formed. Three variants of reducing signatures to sizes were used for classification: 128×128, 256×256 and 512×512 pixels. These images served as the source data for the convolutional neural network.As a result of testing the proposed approach, the average accuracy of the correct classification was achieved on medium-sized images and is equal to 93.33%.

In the process of handwritten signature recognition, preprocessing is an important step before calculation its informative features. Signatures of any person always have some differences, in addition, they can be of different colors, sizes and orientations. After signature digitization, their images may contain some noise. The purpose of signature image preprocessing is to obtain the most invariant representation of the digital image of a person's signature, which will allow us to identify him or define that the signature is forged.This paper describes a sequence of transformations necessary to perform preprocessing of the signature image and form its representation of a single orientation and size. It is assumed that there are no graphic elements in the image that are not related to the signature and the background is relatively uniform. The transformations under consideration sequentially perform binarization of the signature image, its filtering, rotation, cropping of the circumscribed rectangle and scaling to a fixed size.The described preprocessing procedures were applied to a number of available digital signature image databases, such as CEDAR, BHSig260-Bengali, BHSig260-Hindi. Experiments on signature recognition confirm that the presented approach to the signature image preprocessing leads to increasing of the recognition accuracy.

In this paper, a method for estimating the distance to the object guided along a hyperbola to a target using a bistatic hyperbolic navigation system on a plane is given. At the same time, to solve the guidance problem, the number of required navigation positions is reduced by one in comparison with the classical method of hyperbolic navigation. However, in the guidance algorithms, it is still required to estimate the distance of the targeted object from the center of the base, the methods of obtaining which are considered in the work.

This paper discusses a new automated training system called CATS. The proposed system covers all the main components of the educational process, including the simple and convenient formation of educational material, tasks for laboratory works, tests to check knowledge, allows you to monitor the progress of students, the process of studying educational content, check completed work for plagiarism, send incorrectly completed tasks to correction, keep an electronic journal and much more. The automated CATS system has been introduced into the educational process at the Belarusian National Technical University and is actively used, especially in the context of the COVID-19 pandemic. In the spring of 2020 alone, more than a thousand users have registered in the CATS system. The intellectual component in the CATS system allows you to implement a unique training program, which is based on the existing knowledge and the level of perception of the educational material by the students. As mathematical methods, it is proposed to use the analysis of expert systems, as well as artificial neural networks. These mathematical methods made it possible to develop adaptability algorithms, their software implementation and testing in the educational process. Users are provided with a web application and its mobile clients for iOS and Android operating systems. Mobile applications are localized in Russian, Belarusian, English and German. By formalizing the intellectual processes that are carried out by both the teacher and the student, it is possible to automate a certain part of their functions, reduce the cost of manual labor, which will make it easier to control the educational process, and make the training itself more effective.

The goal of the studies described in the paper is to find a quantitative assessment that maximally correlates with the subjective assessment of the contrast image quality in the absence of reference image. As a result of the literature analysis, 16 functions were selected that are used for no-refernce image quality assessment: BEGH, BISH, BREN, CMO, CURV, FUS, HELM, EBCM, KURT, LAPD, LAPL, LAPM, LOCC, LOEN, SHAR, WAVS. They all use the arithmetical mean of the local contrast quality. As an alternative to averaging local estimates (since the mean is one of two parameters of the normal distribution), it is proposed to use one of two parameters of the Weibull distribution of the same data – scale or shape.For the experiments, digital images with nonlinear contrast distortion from the available CCID2014 database were used. It contains 15 original images with a size of 768x512 pixels and 655 versions with modified contrast. This database of images contains the average visual quality assessment (Mean Opinion Score, briefly MOS) of each image. Spearman’s rank correlation coefficient was used to determine the correspondence between the visual MOS scores and the studied quantitative measures.As a result of the research, a new quality assessment measure of contrast images in the absence of references is presented. To obtain the estimate, local quality values are calculated by the BREN measure, their set is described by the Weibull distribution, and the scale parameter of the distribution serves as the best numerical estimate of the quality of contrast images. This conclusion is confirmed experimentally, and the proposed measure correlates better than other variants with the subjective assessments of experts.

The paper considers a problem of optimal feature selection for resume data processing by means of combining multicriteria evaluation technique and hierarhical classifying trees technology what makes it possible to build a selection mechanism without necessity to collect data for the learning purposes of real applicants. Instead, the learning data are generated by means of the technique used in a full factorial experiment with quite a restricted number of samples. The suggested approach minimizes the number of the features used in selection the best candidates and does not use the quantitative ratings of candidates replacing them with multi-phases classifying procedure. These peculiarities of the suggested selection mechanism make it more flexible and form a basis for applying it in conditions characterized by vagueness and fuzziness of the applicant data.

The aim of the work is to limit excessive thinning and increase the resistance to contour noise of skeletons resulted from arbitrary binary image shape while maintaining a high skeletonization rate. The skeleton is a set of thin lines, the relative position, the size and shape, which conveys information of size, shape and orientation in space of the corresponding homogeneous region of the image. To ensure resistance to contour noise, skeletonization algorithms are built on the basis of several steps. Zhang-Suen algorithm is widely known by high-quality skeletons and average performance, which disadvantages are the blurring of diagonal lines with a thickness of 2 pixels and the totally disappear patterns of 2x2 pixels. To overcome them, a mathematical model that compensates the Zhang-Suen algorithm has proposed in this paper, along with a producing mask and two logical conditions for evaluating its elements.

Problem of estimation of variated frequency of components of polyharmonic signals has been arose. Three-dimensional time-frequency representation of signals is usually used to resolve this problem. But simple and reliable method of instantaneous frequency tracking is needed. Frequency tracking method based on estimation of shifts of peaks of spectrogram has been proposed in this paper. It is assumed that shift of spectral peaks of components of signal is proportional to variation of fundamental frequency. Logarithmic scaling of time-frequency representation is used to make spectral peaks equidistant. Temporal dependence of shift of spectral maximums is obtained using correlation of windowed spectrum at the first frame and spectrum of signal in the current window. Then obtained track is translated in linear scale. Proposed method does not estimate values of instantaneous frequency or central frequency of signal component but estimates its variation. Advantage of the method is that it can estimate frequency track even if range of frequency variation and its central value are known roughly or unknown at all. Multiple components do not interfere to estimate fundamental frequency variation. Reduction of bandwidth is recommended to increase accuracy of frequency track estimation, but analysis of time-frequency representation containing a few components is also possible. Dependency of performance of analysis of synthetic signals using the method on various signal to noise ratios under different conditions was estimated. Applicability of the method for vibrational diagnosing of rotary equipment was checked out using spectral interference method.

This paper discusses the problem of determining a kinematics (in terms of transfer function, as far as possible) of parameters of the motion of an aircraft expressed in the curvilinear coordinate system and control accelerations expressed in a rectangular coordinate system. Examples of curvilinear coordinate systems using in practice can be polar, biangular, two-center bipolar, elliptic, parabolic cylindrical, spherical, ellipsoidal, coordinate systems. A technique for obtaining a kinematic link for the control problem of an unmanned aerial vehicle in the elliptic coordinate system was described. It allowed to obtain simpler view of the kinematic link which could provide navigation an aircraft along the hyperbola deriving from the time difference of arrival navigation system. It can. As a result, it is possible to reduce the number of the navigation radio beacons.

This paper considers the problem of optimal control of branched water supply systems. To control the system, the problem of optimal distribution of products is developed whereas non-linear programming problems are applied. We consider a system for providing products, consisting of magistral and distribution pipelines, taking products from the magistral pipeline. Each distribution line has many warehouses. Products are taken into the system using the main intake facility and transferred between the warehouses using intermediate distribution facilities. To eliminate the deficiencies in management, tasks are set to determine the necessary intensities of product supply in the facilities, allowing timely provision of consumers with the necessary volume of products, to minimize losses, product discharges of facilities in the system during a certain control period.

The partitioning a set of professional programmers into a set of teams when a programming project specifies requirements to the competency in various programming technologies and tools is a hard combinatorial problem. The paper proposes a genetic algorithm, which is capable of finding competitive and high-quality partitioning solutions in acceptable runtime. The algorithm introduces chromosomes in such a way as to assign each programmer to a team, define the team staff and easily reconstruct the teams during optimization process. A fitness function characterizes each chromosome with respect to the quality of the programmers partitioning. It accounts for the average qualification of teams and the qualification of team best representatives on each of the technologies. The function recognizes the teams that meet all constraints on the project and are workable from this point of view. It is also capable of recognizing the teams that do not meet the constraints and are unworkable. The algorithm defines the genetic operations of selection, crossing and mutation in such a way as to move programmers from unworkable to workable teams, to increase the number of workable teams, to ex-change programmers among workable teams, to increase the competency of every workable team, and thus to maximize the teams overall qualification. Experimental results obtained on a set of programmers graduated from Belarus universities show the capability of the genetic algorithm to find good partitioning solutions, maximize the teams’ competency and minimize the number of unemployed programmers.

The paper suggests that the use of classical wavelets may be auxiliary in the analysis of a periodic signal. This is because the intuitive interpretation of the wavelet transform is not obvious. It is proposed to consider the Fourier transform as the main tool in applied research of periodic signals. An example is provided to support this point of view. To isolate the periodic component of the signal, along with wavelet analysis, it is proposed to perform spectral analysis. To do this, pre-filtering is performed using singular wavelets. This approach can significantly complement classical wavelet analysis.

In this paper, the influence of various types of distortion of an image on its quality while reducing its sizes, is investigated. To assess the image quality, it is proposed to use the method of comparison with the standard using a previously developed measure based on the proximity of the values of the parameters of the Weibull distribution, which describes the gradient field of the image. The well-known TID2013 image database was used as the material, which includes 3000 images distorted by 24 types of distorting algorithms with five levels. Each image of the base was reduced by 2, 4 and 8 times by the two most common methods and compared with the original image-original. The calculations were performed for five types of distortions implemented in the database. To make a decision on the acceptability of the applied quality measure, the calculated measure values were compared with the subjective quality ratings provided along with the documentation on the TID2013 database. The comparison was carried out using Spearman’s correlation coefficient. It is shown that the average values of correlations for all images at three types of distortions are very high, while for the other two they are unacceptably low. An attempt has been made to explain this situation by the properties of distorting algorithms that change the structural properties of the image to varying degrees.The possibility of comparing images of the same scene, but with different resolutions, is demonstrated.