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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.

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.

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 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 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 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.

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

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.

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.

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.

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.

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 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.

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.

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.

This paper focuses on the Translation Lookaside Buffer (TLB) management as part of memory management. TLB is an associative cache of the advanced processors, which reduces the overhead of the virtual to physical address translations. We consider challenges related to the design of the TLB management subsystem of the OS kernel on the example of the IA-32 platform and propose a simple model of complete and consistent policy of TLB management. This model can be used as a foundation for memory management subsystems design and verification.

The aim of the work is to develop an algorithm for extracting local extremes of images with low computational complexity and high accuracy. The known algorithms for block search for local extrema have low computational complexity, but only strict maxima and minima are distinguished without errors. The morphological search gives accurate results, highlighting the extreme areas formed by non-severe extremes, however, it has high computational complexity. The paper proposes a block-segment search algorithm for local extremums of images based on an analysis of the brightness of adjacent pixels and regions. The essence of the algorithm is to search for single-pixel local extremes and regions of uniform brightness, comparing the values of their boundary pixels with the values of the corresponding pixels of adjacent regions: the region is a local maximum (minimum) if the values of all its boundary pixels are larger (smaller) or equal to the values of all adjacent pixels. The developed algorithm, as well as the morphological search algorithm, allows detecting all single-pixel local extremes, as well as extreme areas, which exceeds the block search algorithms. At the same time, the developed algorithm in comparison with the morphological search algorithm requires much less time and RAM.

Caches are intermediate level between fast CPU and slow main memory. It aims to store copies of frequently used data and to reduce the access time to the main memory. Caches are capable of exploiting temporal and spatial localities during program execution. When the processor accesses memory, the cache behavior depends on if the data is in cache: a cache hit occurs if it is, and, a cache miss occurs, otherwise. In the last case, the cache may have to evict other data. The misses produce processor stalls and slow down the computations. The replacement policy chooses a data to evict, trying to predict the future accesses to memory. The hit and miss rate depends on the cache type: direct mapped, set associative and fully associative cache. The least recently used replacement policy serves the sets. The miss rate strongly depends on the executed algorithm. The all pairs shortest paths algorithms solve many practical problems, and it is important to know what algorithm and what cache type match best. This paper presents a technique of simulating the direct mapped, k-way associative and fully associative cache during the algorithm execution, to measure the frequency of read data to cache and write data to memory operations. We have measured the frequencies versus the cache size, the data block size, the amount of processed data, the type of cache, and the type of algorithm. After comparing the basic and blocked Floyd-Warshall algorithms, we conclude that the blocked algorithm well localizes data accesses within one block, but it does not localize data dependencies among blocks. The direct mapped cache significantly loses the associative cache; we can improve its performance by appropriate mapping virtual addresses to physical locations.

The aim of this work is to reduce the computational complexity of lossless compression in the spatial domain due to the combined coding (arithmetic and Run-Length Encoding) of a series of bits of bit planes. Known effective compression encoders separately encode the bit planes of the image or transform coefficients, which leads to an increase in computational complexity due to multiple processing of each pixel. The paper proposes the rules for combined coding and combined encoders for bit planes of pixel differences of images with a tunable and constant structure, which have lower computational complexity and the same compression ratio as compared to an arithmetic encoder of bit planes.

The paper proposed a mathematical model that describes the dynamics of the physiological process of milk secretion in the cow’s udder, depending on the value of the time interval that has passed since the end of the last milking. The intensity of this process, and, consequently, the cow’s milk production level, depends, among other things, on the optimal choice of the multiplicity of milkings per day with certain time intervals between milkings. The proposed model will allow to take into account these factors in the analysis and optimization of conditions for the maintenance of dairy cattle herds. The results of the research are applicable in diagnosing the state of a cow, in a comparative assessment of the effectiveness of milking multiplicity, etc. The model’s determination coefficient is 0.82 for the aperiodic link used as a model. The advantage of the proposed approach to the identification of a biological object – a cow – is the use of a passive experiment technique based on statistical processing of experimental data on yields recorded by modern information systems for the management of cattle on existing dairy farms.

With the significant growth of the semiconductor industry, creating small devices with powerful processing ability and network capabilities are no longer a dream for engineers. Currently, Internet of Things (IoT) has become one of the hottest topics in both industry and academia of wireless communication field. The idea of the Internet of Things (IoT) is to connect every day physical objects such as microwave, doors, lightings and so on. The technical concept of the IoT is to enables these different physical objects to sense information using sensors and sends this information to a server. Industrial IoT is to integrate various technologies to improve business services in different sectors. It implicitly indicates the behavior of machine-to-machine communications. Each of industrial IoT as service domains has its own communication requirements that are measured differently in both such as reliability, Quality of service (QoS), and privacy. According to the development of industrial automation, the industrial Internet of things (IoT) is widely used in smart factories to capture the data and manage the production. One of the most important components of industrial IoT is the wireless sensor network (WSN), which are easy to deploy and use in indoor industrial environments for a IoT of tasks, such as irrigation, machine condition monitoring, and environment monitoring. There are a IoT of works focusing on the WSN in industrial IoT. For example, in, a WSN-based hidden Markov model is proposed to estimate the occupancy in the building (also see other works [1], [2]). In this paper, the research focus on 3-D mobile robot tracking in 5G wireless communication combine to sensor network and mobile robot path planning. The mobile robot can move fast in the three-dimensional (3-D) indoor industrial environment for many tasks such as the monitoring of possible damages on industrial plants [3], data gathering and transmission from wireless communication [4], transportation [5].

The central object of computer lexicography is a computer or electronic dictionary, which must have a sufficiently large vocabulary, provide the consistent extraction of information depending on the user’s need and provide complete grammatical information about the words of input and output languages. Taking into account the current trend in the development of special terminological dictionaries, the authors propose an English-Belarusian-Russian dictionary of technical terms. At the initial stage of the work the dictionary was named TechLex and covers the following subject areas: architecture and construction, water supply, information technology, pedagogy, transport communications, economics, energy-supply. Currently, each subject area of the dictionary is located in the Internet GoogleTable and contains about 1000 terms. It has the possibility to be simultaneously filled by several teachers. The linguistic database of the dictionary is not created by the traditional way of processing a large number of paper dictionaries and combining the received translations. Lexis from sequential processing of scientific and technical English periodicals of particular subject areas is the base of it. The software of the proposed electronic dictionary is designed taking into account the analysis of modern electronic multilingual translation dictionaries and is a client-server application in Java programming language. The client part of the system contains a mobile application for the Android operating system, which was tested on tablets and smartphones with different screen diagonals. The interface of TechLex dictionary is designed in such a way that only a single zone is activated according to the query, so there is no need to view all the subject areas of the dictionary. The proposed TechLex dictionary is the first technical multilingual electronic dictionary with an English-Belarusian-Russian version.

The importance of efficient traffic management problem grows every year. Constantly increasing number of vehicles and traffic volume requires improvement of methods and algorithms of traffic control. Such improvement becomes possible due to the spreading of global navigation and positioning systems, the development of wireless communication technologies and mobile internet, the advance in specialized technologies for interaction between vehicles and road infrastructure (V2I), the enhancement of machine learning models, computer vision algorithms, the emergence of driverless cars. This paper considers the novel approach to traffic management at intersection based on the use of V2I communication, describes general scheme of such approach and differences with conventional traffic light regulation. Developed algorithm of intersection management utilizes advantages of V2I communication to increase throughput of the intersection comparing to simple traffic light regulation and more advanced adaptive methods. The increase of throughput is achieved due to the dynamic construction of regulation phases which can be done because of more complete information about traffic flow. The comparence of various methods of regulation was performed in developed traffic simulation environment based on multi-agent approach.

Nowadays, it is considerable to develop a general concept and implement a system for storing and analyzing data related to socio-economic displacements of people. The population movement, related to long-term and short-term migrations, has an increasing nature, which directly affects the various fields of activity in a single country and the world community as a whole. The proposed article describes the subject area associated with socio-economic displacements of people, the key features of internal and external migrations are noted. Based on the subject area, the general architecture of the universal system of data storage and processing is proposed, which is based on the client-server architecture. A fragment of the data model, associated with the accumulation of data from external sources, is provided. General approaches of algorithms and data structures usage are proposed. The system architecture is described with the possibility of scaling both vertical and horizontal.The proposed system organizes the process of searching for data and filling the database from third-party sources. To do this, a module for collecting and converting information from third-party Internet sources and sending them to the database has developed. In the paper is noted the feature of the client application, which provides a convenient interface for analyzing data in the form of diagrams, graphs, maps, etc. The system is intended for various users interested in analyzing economic and social transfers, for example, to tourist organizations wishing to obtain statistics for a certain time, to airlines which could plan flights in one direction or another, as well as for state structures with the purpose of analyzing the migration flows of the population and developing appropriate strategy for their regulation.

The aim of this paper is the linear synthesis of two loops SISO systems with discreet time proportional integral (PI) controllers. This linear synthesis is dedicated for the systems with plant parameters uncertainty. The synthesis is based on the time scale method, providing the separate slow and fast components of the control low. The PI- controller parameters calculation is based on the modal control and plant model reduction. The conditions carried out for the each control loop dynamics still similar to the second order one. The discrete time microcontroller based numerical control restricts the stability domain of the system and each control loop in it. The stability domain of each loop is the round on the complex plane with radius, depending on the time period. Each inner loop must be more fast, then each outer one. Hence, in the outer loop the time period, required for the PI controller reaction computation, can be more then in the inner loop. This PI- controller parameter calculation method is approximate, and it is efficient for the systems, whose dynamics contains the slow and fast components. In particular, the electrical drives control systems contain the fast electromagnetic component and the slow mechanical part. The effectiveness of this method is illustrated by the example and simulation.

The main advantage of using information technologies in education, which consists in speeding up and simplifying of information exchange, is also its drawback, because it raises the problem of plagiarism. The purpose of this paper is to develop testing text software for uniqueness in learning management systems. To achieve this goal, it is necessary to solve a range of problems related to the choice of a method for determining plagiarism, its algorithmization and software implementation. The work deals with the methods of shingles, super-shingles, signature methods, vector models of text representation, as well as cluster analysis of text information. The authors suggest a modification of the vector model to improve the accuracy of determining similar documents by creating an N-list of each document separately. As a result, a pairwise comparison of the documents and the formation of the image of one document relative to the N-list of the other will occur. Thus, in the i-th row of the similarity matrix, the coefficients of similarity of all the documents considered relative to the i-th document will be recorded. The proposed modification will also speed up the calculation process, since there is no need to search for common terms for all documents. To analyze a large number of student’s works in order to test them for plagiarism, the authors propose using a cluster approach. Its application showed that the time for determining duplicates for one document and for all documents included in the sample is the same. For the same time it is possible to get all the options for the same works of students. Thus, the use of cluster analysis of text information in determining plagiarism significantly saves both the teacher’s time and computing resources. The software implementation of the proposed algorithms is implemented as a web service in the Java language.

The paper presents results of our experiments on compression of the high dynamic range SAR images. The range is equal to 16-bit. Objectives of study were comparison of known approaches to compression of the high dynamic range images; selection of optimal parameters for compression algorithms, and selection of a no-reference measure for image quality assessment after compression. Tone-mapping transformations like gamma correction, Ashikhmin-operator, mu-transformation, as well as no-reference image quality assessment measures were tested. The results of the experiments are presented in the article. It was concluded that further research and analysis of various functions and approaches to compression of dynamic range of SAR images is necessary, since including in the article approaches do not give stable and positive results on all SAR images. It was also concluded that after transformation 16-bit images, it is very difficult to estimate which image is better, and it is necessary to use no-reference image quality assessment measure.

Artificial neural networks (ANN) are now widely used in control and forecasting problems. The purpose of this work is the implementation of an artificial neural network for virtual objects control in a computer game of football. To achieve this goal, it is necessary to solve a number of problems related to mathematical modeling of ANN, algorithmization and software implementation. The paper deals with the mathematical modeling of an artificial neural network by the method of back propagation of an error, the algorithms for calculating neurons and for teaching ANN are presented. The software implementation of the artificial neural network was performed in the JavaScript language using the Node. js library, which assumed the role of a server for managing the game process. Some functions of the Underscore. js library were used to work with data arrays. The training sample consisted of more than 1000 sets of inputs and outputs, reflecting all possible situations. The results of software implementation of an artificial neural network are described on the example of virtual players control for a computer game. The results of the work show that ANN with a sufficiently high speed in real time gives the necessary direction for the player’s movement. The use of an artificial neural network has reduced the use of CPU time, which is extremely important in problems where rapid decision making is required, because complex calculations and prediction algorithms can not always be invested in 20 ms, which is fraught with skipping moves and losses. The simulated artificial neural network and the implemented algorithm of its learning can be used to solve other problems, for which only new data of the surrounding world are needed.

The paper presents an attempt to apply of evolutionary methods to the design and training of a system for recognizing distorted text.Over the past decades, artificial neural networks are widely used in many areas of artificial intelligence, such as forecasting, optimization, data analysis, pattern recognition and decision making. Nevertheless, the traditional heuristic approaches to design of multi-layer neural networks are based on the recombination of already existing neural network architectures.This approach allows us to solve a wide range of problems, but implies compliance with specific conditions for the quality work of algorithms.The natural analogues of such intelligent systems in living nature, however, are universal enough to adapt to virtually any habitat.Despite their extreme complexity and limited ability to study their structures, it is known that these structures were formed as a result of the evolutionary process. And if today it is impossible to determine the exact architecture of the links in biological neural systems, then at least one can try to reproduce the very process of their formation in order to obtain a more universal algorithm than those developed to the present moment.In opposite to them we form the final structure of the core of the classification system by evolutionary process, taking into account the knowledge about the features of the development and construction of the nervous system of vertebrates.Applying of the approach makes it possible to abstract from the limitations of existing neural network algorithms, caused by the scope of application of specific types of their structures.

Further development of cryptographic algorithms based on the principles of many-valued logic requires more accurate research of non-binary cryptographic primitives – S-boxes. One of the most promising constructions for the synthesis of S-boxes is the Nyberg construction, which ensures high quality of the designed S-boxes in the binary case. The disadvantage of the Nyberg construction is the small cardinality of the classes of the constructed S-boxes. Nevertheless, this disadvantage can be overcome by considering all the isomorphic representations of the main field, substantially expanding the choice of available high-quality S-boxes. The research carried out in this paper has shown that the advantages of the Nyberg construction can be easily transferred to a many-valued case. Thus, we construct complete sets of S-boxes of the Nyberg construction over all isomorphic representations of fields GF(pᵏ), р = 3,5, and research their nonlinear characteristics. As a criterion of nonlinearity, we measure the distances from the component many-valued functions to the set of Vilenkin–Chrestenson functions that are considered to be the most linear. The correlation coefficients of the output and input vectors of the obtained S-boxes are calculated. The researches performed have shown the high quality of the constructed cryptographic primitives and allow recommendation of them for use in cryptoalgorithms based on the principles of many-valued logic.