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This paper is devoted to the development of general algorithm for solving to the stability problem of anisotropic plates using the additional load discretization method. The study of the stability problem is relevant for all types of structural elements and machine parts, and its importance is especially increasing with respect to anisotropic thin plates. This is due to the fact that with the use of new structures and materials, the material intensity is reduced, the area of application of thin-walled systems with low stiffness, for which the danger of elastic loss of stability increases, and, therefore, the importance and relevance of the theory and methods of practical solution of problems of elastic stability of such structures increases. In many works, analytical expressions for determination of critical load are given. At present, the determination of critical loads causes great difficulties in their numerical determination. Therefore, the article presents the most effective numerical and analytical solution of this problem. As a rule, to solve stability problems of anisotropic plates, different representations of the bending deflection function in different rows are used. But the use of such representations is justified only under certain boundary conditions and under the condition of uniformly distributed load. The study described in this paper offers a way to overcome these difficulties, allowing the numerical values of critical forces to be determined without much difficulty. With increasing grid density, the accuracy of the critical load value increases rapidly and with an 8×8 grid, the deviation from the exact solution equal to is 1 %. From a practical point of view, the discovered mechanism of numerical realization of this problem allows to improve engineering design calculations of stability of anisotropic plates with different conditions on supports and with different loading. [ABSTRACT FROM AUTHOR]

The object of this study is a clustering algorithm using various technologies. This paper compares clustering algorithms that are more commonly used to analyze urban road network trajectories, the growth curve model, with the elbow method and the x-means algorithm. Experiments were conducted with various volumes of big data to determine calculation time, accuracy, and ways to increase calculation time. These results can be used to manage traffic jams in congested areas and city streets. Considering the widespread use of clustering algorithms for solving various problems, this study proposes to introduce GCM, SPGK methods for monitoring and analyzing the state of congestion on city roads. The work was carried out in the following steps: research and selection of methods based on efficiency and time, implementation of parallel computing technologies to improve computation speed, demonstration of the selected method based on collected data from a real city with visualization of the results. The growth curve model algorithm has been proven to be almost 5 times more effective than the elbow method and the x-means algorithm. The time allocated for data processing has been calculated. An increase in the volume of processed data showed an almost stable execution time t=3 s for the GCM algorithm for data with a volume of up to almost 2,000 units. The effectiveness of SPGK-means was shown for different values of the number of points. Models of the Chengdu transport network obtained using a clustering algorithm with maximum grid density of neighborhoods are presented. There are some deviations between the grid and the road network due to the large grid size. This error is explained by an error of up to one between the points and the real grid. The results obtained clearly show how optimization of congested roads can be influenced. They provide information to obtain data on available routes, which allows you to analyze the road network individually and as a whole. [ABSTRACT FROM AUTHOR]

The Kalman filter algorithm is very important as a recursive algorithm method to optimize sensor output from physical parameter measurement systems, especially physics practicum demonstration systems. One of the distance parameter measurement demonstration systems used in Hooke’s law demonstration system is applied in physics practicum, the system has problems related to fluctuating or unstable sensor output. This research implements the Kalman filter algorithm on the Arduino IDE sketch to reduce noise that appears at the ultrasonic sensor output. The methodology used in this study includes the application of the Kalman filter algorithm to the Arduino IDE sketch with the variable value of the Kalman filter algorithm equation modified with a value of R=10, H=1, and Q=1, and returns the filtered Kalman out value. The Arduino output results are exported to Ms. Excel for further analysis and generate a filtered ultrasonic sensor output signal graph compared without using the Kalman filter. The ultrasonic sensor output noise filtration effectively reduces noise by showing a decrease in the mean squared error (MSE) value and obtaining the best performance of up to 89.23 %. The accuracy of Kalman filter filtration results can be seen from the calculation that the spring constant of filtered metal materials is smaller than the conventional measurement spring constant. Accurate and effective results with the implementation of the Kalman filter algorithm can be developed for the variation values of distance parameters and Kalman filter algorithm variables (R, Q, and H) with other value variations, especially variables that produce filtering curves close to straight lines. It was concluded that the Kalman filter algorithm was able to improve the performance of Hooke’s law prop system. [ABSTRACT FROM AUTHOR]

The problem of oil displacement was solved using neural networks and machine learning classifiers. The Buckley Leverett model is selected, which describes the process of oil displacement by water. It consists of the equation of continuity of oil, water phases and Darcy’s law. The challenge is to optimize the oil displacement problem. Optimization will be performed at three levels: vectorization of calculations; implementation of classical algorithms; implementation of the algorithm using neural networks. A feature of the method proposed in the work is the identification of the method with high accuracy and the smallest errors, comparing the results of machine learning classifiers and types of neural networks. The research paper is also one of the first papers in which a comparison was made with machine learning classifiers and neural and recurrent neural networks. The classification was carried out according to three classification algorithms, such as decision tree, support vector machine (SVM) and gradient boosting. As a result of the study, the Gradient Boosting classifier and the neural network showed high accuracy, respectively 99.99 % and 97.4 %. The recurrent neural network trained faster than the others. The SVM classifier has the lowest accuracy score. To achieve this goal, a dataset was created containing over 67,000 data for class 10. These data are important for the problems of oil displacement in porous media. The proposed methodology provides a simple and elegant way to instill oil knowledge into machine learning algorithms. This removes two of the most significant drawbacks of machine learning algorithms: the need for large datasets and the robustness of extrapolation. The presented principles can be generalized in countless ways in the future and should lead to a new class of algorithms for solving both forward and inverse oil problems. [ABSTRACT FROM AUTHOR]

The object of research in the paper is extrapolation problems based on interpolation polynomials. Polynomial-based prediction methods are well known. However, the problem is that such methods often give very large errors in practice. The permissible error of extrapolation even by one grid step is not ensured by the high accuracy of interpolation using polynomials. The paper proposes an algorithm that allows to significantly improve polynomial forecasts by optimizing the procedure for choosing the power of the polynomial, on the basis of which the forecast is built. The algorithm is based on the procedure for building all polynomial forecasts according to known data and analysis of these forecasts. In particular, the presence of monotonicity and a tendency to convergence allows determining the optimal degree of the polynomial. In the absence of monotonicity, provided that certain ratios are met, the forecast can be constructed as the arithmetic average of all polynomial forecasts. An important result is the estimation of the error of the forecasting method by averaging polynomial forecasts. The development of the algorithm became possible due to the use of a special method of constructing a one-step polynomial forecast. The method differs in that it allows to build a forecast without using the cumbersome procedure of calculating the unknown coefficients of the polynomial. The numerical results presented in the work demonstrate the effectiveness of the forecasting technique based on the average of polynomial forecasts. In particular, for the test functions, the relative error was about 2–5 %, while polynomials of different degrees in the worst case yielded more than 50 %. The obtained results can be useful for building shortterm forecasts of series of economic dynamics, forecasting the behavior of arbitrary processes with a dominant deterministic component. [ABSTRACT FROM AUTHOR]

The paper presents a new method for solving the 0–1 linear programming problems (LPs). The general 0–1 LPs are believed to be NP-hard and a consistent, efficient general-purpose algorithm for these models has not been found so far. Cutting planes and branch and bound approaches were the earliest exact methods for the 0–1 LP. Unfortunately, these methods on their own failed to solve the 0–1 LP model consistently and efficiently. The hybrids that are a combination of heuristics, cuts, branch and bound and pricing have been used successfully for some 0–1 models. The main challenge with these hybrids is that these hybrids cannot completely eliminate the threat of combinatorial explosion for very large practical 0–1 LPs. In this paper, a technique to reduce the complexity of 0–1 LPs is proposed. The given problem is used to generate a simpler version of the problem, which is then solved in stages in such a way that the solution obtained is tested for feasibility and improved at every stage until an optimal solution is found. The new problem generated has a coefficient matrix of 0 s and 1 s only. From this study, it can be concluded that for every 0–1 LP with a feasible optimal solution, there exists another 0–1 LP (called a double in this paper) with exactly the same optimal solution but different constraints. The constraints of the double are made up of only 0 s and 1 s. It is not easy to determine this double 0–1 LP by mere inspection but can be obtained in stages as given in the numerical illustration presented in this paper. The 0–1 integer programming models have applications in so many areas of business. These include large economic/ financial models, marketing strategy models, production scheduling and labor force planning models, computer design and networking models, military operations, agriculture, wild fire fighting, vehicle routing and health care and medical models [ABSTRACT FROM AUTHOR]

This paper investigates the construction of randomstructure LDPC (low-density parity-check) codes using Progressive Edge-Growth (PEG) algorithm and two proposed algorithms for removing short cycles (CB1 and CB2 algorithm; CB stands for Cycle Break). Progressive Edge-Growth is an algorithm for computer-based design of random-structure LDPC codes, the role of which is to generate a Tanner graph (a bipartite graph, which represents a parity-check matrix of an error-correcting channel code) with as few short cycles as possible. Short cycles, especially the shortest ones with a length of 4 edges, in Tanner graphs of LDPC codes can degrade the performance of their decoding algorithm, because after certain number of decoding iterations, the information sent through its edges is no longer independent. The main contribution of this paper is the unique approach to the process of removing short cycles in the form of CB2 algorithm, which erases edges from the code’s parity-check matrix without decreasing the minimum Hamming distance of the code. The two cycleremoving algorithms can be used to improve the errorcorrecting performance of PEG-generated (or any other) LDPC codes and achieved results are provided. All these algorithms were used to create a PEG LDPC code which rivals the best-known PEG-generated LDPC code with similar parameters provided by one of the founders of LDPC codes. The methods for generating the mentioned errorcorrecting codes are described along with simulations which compare the error-correcting performance of the original codes generated by the PEG algorithm, the PEG codes processed by either CB1 or CB2 algorithm and also external PEG code published by one of the founders of LDPC codes [ABSTRACT FROM AUTHOR]

Copyright of Technology Audit & Production Reserves is the property of PC TECHNOLOGY CENTER and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Eastern-European Journal of Enterprise Technologies is the property of PC TECHNOLOGY CENTER and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, the object of the study is determining air traffic scheduling management by optimizing mathematical models. The problem in this study is that the COVID-19 pandemic has significantly disrupted air traffic, resulting in changes to regulations, travel restrictions and a decrease in passenger demand. One of the problems that must be resolved is how to organize and adapt flight schedules to current conditions by focusing on mathematical models that are used to optimize or increase the efficiency of managing flight schedules or air traffic. Mathematical models can help find ways to optimize the use of available resources, such as airport capacity, flight routes and flight frequency. The results obtained in this research are a mathematical model that specifically takes into account the variables involved in setting air traffic schedules during the COVID-19 pandemic so that capacity limits at airports and airspace are always normal. An optimization model was developed from previous research, namely the model that takes into account ground and air delays as well as the use of alternative paths and avoids deviations from the initial more accurate flight plan, which overall indicates that the maximum time and maximum distance values for each item have been optimized to achieve better values. This research has the novelty of producing a mathematical model using variables, objective functions, capacity limits, flight structure limits and variable domains, which then produces an algorithm with data input processes, determining optimization models, determining variables, determining objective functions, determining problems. The results of this model can be recommended to airlines in scheduling flights during the pandemic [ABSTRACT FROM AUTHOR]

This paper reports an analysis of the software (SW) safety testing techniques, as well as the models and methods for identifying vulnerabilities. An issue has been revealed related to the reasoned selection of modeling approaches at different stages of the software safety testing process and the identification of its vulnerabilities, which reduces the accuracy of the modeling results obtained. Two steps in the process of identifying software vulnerabilities have been identified. A mathematical model has been built for the process of preparing security testing, which differs from the known ones by a theoretically sound choice of the moment-generating functions when describing transitions from state to state. In addition, the mathematical model takes into consideration the capabilities and risks of the source code verification phase for cryptographic and other ways to protect data. These features generally improve the accuracy of modeling results and reduce input uncertainty in the second phase of software safety testing. An advanced security compliance algorithm has been developed, with a distinctive feature of the selection of laws and distribution parameters that describe individual state-to-state transitions for individual branches of Graphical Evaluation and Review Technique networks (GERT-networks). A GERT-network has been developed to prepare for security testing. A GERT-network for the process of checking the source code for cryptographic and other data protection methods has been developed. A graphic-analytical GERT model for the first phase of software safety testing has been developed. The expressions reported in this paper could be used to devise preliminary recommendations and possible ways to improve the effectiveness of software safety testing algorithms [ABSTRACT FROM AUTHOR]

The object of research of this work is the methods of deep learning for source code vulnerability detection. One of the most problematic areas is the use of only one approach in the code analysis process: the approach based on the AST (abstract syntax tree) or the approach based on the program dependence graph (PDG).In this paper, a comparative analysis of two approaches for source code vulnerability detection was conducted: approaches based on AST and approaches based on the PDG.In this paper, various topologies of neural networks were analyzed. They are used in approaches based on the AST and PDG. As the result of the comparison, the advantages and disadvantages of each approach were de-termined, and the results were summarized in the corresponding comparison tables. As a result of the analysis, it was determined that the use of BLSTM (Bidirectional Long Short Term Memory) and BGRU (Bidirectional Gated Linear Unit) gives the best result in terms of problems of source code vulnerability detection. As the analysis showed, the most effective approach for source code vulnerability detection systems is a method that uses an intermediate representation of the code, which allows getting a language-independent tool.Also, in this work, our own algorithm for the source code analysis system is proposed, which is able to perform the following operations: predict the source code vulnerability, classify the source code vulnerability, and generate a corresponding patch for the found vulnerability. A detailed analysis of the proposed system’s unresolved issues is provided, which is planned to investigate in future researches. The proposed system could help speed up the software development process as well as reduce the number of software code vulnerabilities. Software developers, as well as specialists in the field of cybersecurity, can be stakeholders of the proposed system. [ABSTRACT FROM AUTHOR]

In a variety of engineering, scientific challenges, mathematics, chemistry, physics, biology, machine learning, deep learning, regression classification, computer science, programming, artificial intelligence, in the military, medical and engineering industries, robotics and smart cars, fuzzy nonlinear equations play a critical role. As a result, in this paper, an Optimization Algorithm based on the Euler Method approach for solving fuzzy nonlinear equations is proposed. In mathematics and computer science, the Euler approach (sometimes called the forward Euler method) is a first-order numerical strategy for solving ordinary differential equations (ODEs) with a specified initial value. The local error is proportional to the square of the step size, while the general error is proportional to the step size, according to the Euler technique. The Euler method is frequently used to create more complicated algorithms. The Optimization Algorithm Based on the Euler Method (OBE) uses the logic of slope differences, which is computed by the Euler approach for global optimizations as a search mechanism for promising logic. Furthermore, the mechanism of the proposed work takes advantage of two active phases: exploration and exploitation to find the most important promising areas within the distinct space and the best solutions globally based on a positive movement towards it. In order to avoid the solution of local optimal and increase the rate of convergence, we use the ESQ mechanism. The optimization algorithm based on the Euler method (OBE) is very efficient in solving fuzzy nonlinear equations and approaches the global minimum and avoids the local minimum. In comparison with the GWO algorithm, we notice a clear superiority of the OBE algorithm in reaching the solution with higher accuracy. We note from the numerical results that the new algorithm is 50 % superior to the GWO algorithm in Example 1, 51 % in Example 2 and 55 % in Example 3. [ABSTRACT FROM AUTHOR]

Lightweight encryption algorithms are considered a relatively new direction in the development of private key cryptography. This need arose as a result of the emergence of a large number of devices with little computing power and memory. Therefore, it became necessary to develop algorithms that can provide a sufficient level of security, with minimal use of resources. The paper presents a new lightweight LBC encryption algorithm. LBC is a 64–bit symmetric block algorithm. It supports 80 bit secret key. The number of rounds is 20. The algorithm has a Feistel network structure. The developed lightweight algorithm has a simple implementation scheme, and the transformations used in this algorithm have good cryptographic properties. This was verified by studying the cryptographic properties of the algorithm using the "avalanche effect" and statistical tests. The avalanche property was checked for each round when each bit of the source text was changed. Based on the work carried out, it was found that the proposed encryption algorithm is effective to ensure a good avalanche effect and the binary sequence obtained after encryption is close to random. Its security against linear and differential cryptanalysis is also evaluated. The results of the research revealed good cryptographic properties of this algorithm. The algorithm will be used for devices with small hardware resources, in information and communication systems where confidential information circulates, and it is also extremely necessary to exchange information in a protected form in an operationally acceptable time. [ABSTRACT FROM AUTHOR]

Copyright of Eastern-European Journal of Enterprise Technologies is the property of PC TECHNOLOGY CENTER and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Eastern-European Journal of Enterprise Technologies is the property of PC TECHNOLOGY CENTER and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper reports a method to solve ordinary fourth-order differential equations in the form of ordinary power series and, for the case of regular special points, in the form of generalized power series. An algorithm has been constructed and a program has been developed in the MAPLE environment (Waterloo, Ontario, Canada) in order to solve the fourth-order differential equations. All types of solutions depending on the roots of the governing equation have been considered. The examples of solutions to the fourth-order differential equations are given; they have been compared with the results available in the literature that demonstrate excellent agreement with the calculations reported here, which confirms the effectiveness of the developed programs. A special feature of this work is that the accuracy of the results is controlled by the number of terms in the power series and the number of symbols (up to 20) in decimal mantissa in numerical calculations. Therefore, almost any accuracy allowed for a given electronic computing machine or computer is achievable. The proposed symbolic-numerical method and the work program could be successfully used for solving eigenvalue problems, in which controlled accuracy is very important as the eigenfunctions are extremely (exponentially) sensitive to the accuracy of eigenvalues found. The developed algorithm could be implemented in other known computer algebra packages such as REDUCE (Santa Monica, CA), MATHEMATICA (USA), MAXIMA (USA), and others. The program for solving ordinary fourth-order differential equations could be used to construct Green’s functions of boundary problems, to solve differential equations with private derivatives, a system of Hamilton’s differential equations, and other problems related to mathematical physics. [ABSTRACT FROM AUTHOR]

Copyright of Eastern-European Journal of Enterprise Technologies is the property of PC TECHNOLOGY CENTER and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Porter stemmer algorithm is a broadly used, however, an essential tool for natural language processing in the area of information access. Stemming is used to remove words that add the final morphological and diacritical endings of words in English words to their root form to extract the word root, i.e. called stem/root in the primary text processing stage. In other words, it is a linguistic process that simply extracts the main part that may be close to the relative and related root. Text classification is a major task in extracting relevant information from a large volume of data. In this paper, we suggest ways to improve a version of the Porter algorithm with the aim of processing and overcome its limitations and to save time and memory by reducing the size of the words. The system uses the improved Porter derivation technique for word pruning. Whereas performs cognitive-inspired computing to discover morphologically related words from the corpus without any human intervention or language-specific knowledge. The improved Porter algorithm is compared to the original stemmer. The improved Porter algorithm has better performance and enables more accurate information retrieval (IR). [ABSTRACT FROM AUTHOR]

Optimization is now considered a branch of computational science. This ethos seeks to answer the question «what is best?» by looking at problems where the quality of any answer can be expressed numerically. One of the most well-known methods for solving nonlinear, unrestricted optimization problems is the conjugate gradient (CG) method. The Hestenes and Stiefel (HS-CG) formula is one of the century’s oldest and most effective formulas. When using an exact line search, the HS method achieves global convergence; however, this is not guaranteed when using an inexact line search (ILS). Furthermore, the HS method does not always satisfy the descent property. The goal of this work is to create a new (modified) formula by reformulating the classic parameter HS-CG and adding a new term to the classic HS-CG formula. It is critical that the proposed method generates sufficient descent property (SDP) search direction with Wolfe-Powell line (sWPLS) search at every iteration, and that global convergence property (GCP) for general non-convex functions can be guaranteed. Using the inexact sWPLS, the modified HS-CG (mHS-CG) method has SDP property regardless of line search type and guarantees GCP. When using an sWPLS, the modified formula has the advantage of keeping the modified scalar nonnegative sWPLS. This paper is significant in that it quantifies how much better the new modification of the HS performance is when compared to standard HS methods. As a result, numerical experiments between the mHSCG method using the sWPL search and the standard HS optimization problem show that the CG method with the mHSCG conjugate parameter is more robust and effective than the CG method without the mHSCG parameter. [ABSTRACT FROM AUTHOR]

This paper proposes a method for protecting the access tokens in client-server data exchange without saving the state based on the formation of the signature of the request using a temporary secret. The devised method allows one not to transfer access tokens with each request, which would make it possible for the attacker to authenticate as a valid user when compromising the connection, for example, when using a «person in the middle» attack. Two variants of the method have been proposed and substantiated – simplified and improved, the scope of which depends on the needs for protection and technical capabilities of their implementation. The robustness of both variants is ensured by the practical inability to select the initial input data of the hash function used to form the signature. The improved version also makes it possible to protect access tokens at the stage of receiving them and provides protection against the attack of the recurrence of the request. Initial user authentication protection is achieved by using the Diffie–Hellman protocol to exchange a secret and access token. Using query IDs and time labels prevents the query from being reused. Advanced security for access tokens is important because having an attacker’s access token gives the attacker full control over the user account. The use of SSL/TLS may not produce the desired level of protection for such important data. It was established that the use of the proposed method does not add significant time costs. The SHA-256 hash function example shows that the relationship between message size and extra time to send and receive a message is linear. When using the proposed method in the browser, the absolute value of additional time spent for messages from 100 bytes to 2,048 KB ranges from 0.4 ms to 142 ms. Given this, the proposed method could be used without significant impact on the experience of use. [ABSTRACT FROM AUTHOR]

The work is devoted to the description of the development of compression algorithms for hyperspectral aerospace images based on discrete orthogonal transformations for the purpose of subsequent compression in Earth remote sensing systems. As compression algorithms necessary to reduce the amount of transmitted information, it is proposed to use the developed compression methods based on Walsh-Hadamard transformations and discrete-cosine transformation. The paper considers a methodology for developing lossy and high-quality compression algorithms during recovery of 85 % or more, taking into account which an adaptive algorithm for compressing hyperspectral AI and the generated quantization table have been developed. The existing solutions to the lossless compression problem for hyperspectral aerospace images are analyzed. Based on them, a compression algorithm is proposed taking into account inter-channel correlation and the Walsh-Hadamard transformation, characterized by data transformation with a decrease in the range of the initial values by forming a set of channel groups [10–15] with high intra-group correlation [0.9–1] of the corresponding pairs with the selection of optimal parameters. The results obtained in the course of the research allow us to determine the optimal parameters for compression: the results of the compression ratio indicators were improved by more than 30 % with an increase in the size of the parameter channels. This is due to the fact that the more values to be converted, the fewer bits are required to store them. The best values of the compression ratio [8–12] are achieved by choosing the number of channels in an ordered group with high correlation. [ABSTRACT FROM AUTHOR]

The paper addresses issues related to the selection of individual indicators to estimate the shape quality of cross-wound packages, as well as the construction of algorithms to determine them automatically. We have developed a method for evaluating the quality of shape of cross-wound packages based on the integrated indicator. To substantiate individual indicators, an expert poll was performed to rank defects in the shape of packages according to the degree of their influence on the suitability of packages for processing at subsequent technological transitions. To quantify each of the specified defect in the shape of a bobbin, we defined individual indicators that make it possible to quantify their impact. We have developed decisive rules and algorithms to calculate them based on the earlier obtained array of data on the coordinates of points at the bobbin’s surface. We have determined a score-based estimate of the influence of each indicator, which characterizes defects in winding, on the suitability of packages for processing at subsequent technological transitions. A comprehensive assessment of the package shape could be obtained using a method of weighted index. The mean weighted index is constructed as a dependence whose arguments are the individual quality parameters and their weighted parameters. Given this, we derived a dependence to calculate the integrated quality indicator of the bobbin’s shape. The higher the value for this indicator, the higher the quality of the controlled package. We have assessed the applicability of the constructed integrated quality indicator to analyzing the shape of packages. To this end, we analyzed a batch of packages, which confirmed the reproducibility of the process of analysis of the package shape using the proposed integrated indicator; as well as correspondence between estimates, derived using the proposed procedure, and visual assessments. A method for the integrated quantification of package shape makes it possible to conduct optimization experiments and to assign, based on them, such adjustable parameters for winding mechanisms that would ensure that packages of the required quality are received. The process of designing new winding equipment could be based on the necessary means to regulate a winding process. [ABSTRACT FROM AUTHOR]

This paper gives examples of the implementation of energy-saving measures in public premises. The introduction of energy-saving measures at enterprises significantly reduces the fixed component of industrial expenditures. As a rule, educational institutions, for example, public premises, are financed from the state budget, and saving money on utilities will enable redirecting finances to the development of the university’s educational and scientific base. Thus, the main purpose of implementing such measures is to reduce the cost of maintaining buildings. The measures are divided into three stages. At the first preparatory stage, the problem elements of a building and communications, which require the introduction of energy-saving measures using a special Fluke Ti25 device, are identified. Problem elements of the building structure were determined by complete scanning of the ceiling, walls, and floor with the help of a thermal imager. A large (more than 10 %) difference between indoor air temperature and the temperature of the building element indicates a problem element. The research method is thermographic. The study contains an example of scanning the wall of the premises. The temperature difference between the left and the right sides of the wall is 2.6 °C (the difference with the room temperature is 21 %). This indicates significant heat losses through the wall. At the second stage of information processing, measures to reduce energy consumption were determined. At the third stage of the introduction of energy-saving measures, the measures that directly affect the energy consumption of a building and effective functioning of communications were implemented. The practical relevance of the study is to obtain results and practical recommendations that can be applied in practice to improve the energy efficiency of premises and buildings [ABSTRACT FROM AUTHOR]

This paper analyzes ways to improve the cryptographic strength of the symmetric block cipher RC5. The task to enhance the stability of the classic RC5 cipher is explained by the fact that it is part of various open cryptographic libraries and is frequently used in practice. Several methods have been considered, applying which theoretically contributes to improving the stability of cryptographic transformations. It is found that unlike other alternatives (increasing the number of rounds, the length of the key, and the encryption block), the use of nonlinear shift functions does not increase the computational complexity of the RC5 algorithm. The study result has helped build an analytical model that was implemented in the form of the MATLAB (USA) software application. The software interface provides the ability to manually change the encryption parameters of the RC5 crypto algorithm. The resulting upgrade of the RC5 crypto algorithm has been tested on different sets of input data during encryption and decryption. The resulting modification also does not lead to an increase in the calculation time but makes it possible to improve the resistance to hacking the encrypted data by several orders of magnitude (210), provided that differential analysis methods are used and the number of rounds is 14. For one of the nonlinear functions used, resistance to the differential cryptoanalysis used increased by 212 times already in the eleventh round of encryption. The reliability of the improved cryptosystem has been confirmed by the absence of statistical correlation between the blocks of incoming messages and output blocks, the absence of collisions at which it is possible to obtain the same sequences of bits at the output with different messages at the input. The resulting algorithm could be applied in computer systems with low computing performance. [ABSTRACT FROM AUTHOR]

The paper considers the features of the formation of an acoustic field by a spherical source with complicated properties in a regular plane-parallel waveguide, which is of practical importance in marine instrumentation and oceanographic research. The calculation algorithm is based on the use of the Helmholtz equation and the Fourier method for each partial region and the conjugation conditions on their boundaries. The presented calculation allows one to get rid of the idealized boundary conditions on the source surface, with the subsequent determination of the excitation coefficients of the waveguide modes within the framework of the Sturm-Liouville problem. In this case, the attraction of the boundary conditions on the surface and the bottom of the sea, as well as the Sommerfeld conditions, makes it possible to obtain the real distribution of the field in the vertical sections of the waveguide. The obtained frequency dependences of the pressure and vibrational velocity components show their amplitude-phase differences, which reach 90 degrees, which partially explains the appearance of singular points in the intensity field in a regular waveguide. It has been determined that multiple reflections of sound waves from the boundaries of the working space and the space of the waveguide cause oscillations of the pressure components with a change in the amplitude level up to 6 dB. It was found that with an increase in the size of the source, a kind of resonance is formed in the working space, the frequency of which depends on the depth of the sea and corresponds to the region kr=x=5.8. It was found that when the acoustic field is formed in the working space, the frequency response of the impedance components is represented as a multiresonant dependence formed on the basis of the frequency characteristics of the lower modes and their combinations. Experimental studies have shown that the results of calculations of the mode composition of the acoustic field of the emitter, obtained in the conditions of the pool, correspond to the spatial characteristics of the mode components of the acoustic field with an error of up to 3 dB. [ABSTRACT FROM AUTHOR]

In most cases, fixed temperature heat detectors are used to detect fire in vehicles. The response parameter of such detectors is constant. The time of fire detection by a fire detector, as well as the probability of its false operation, are affected by heat flux from an internal combustion engine. This paper reports the development and investigation of an operational algorithm of the fixed-dynamic heat detectors with variable response parameters. Depending on the temperature influence exerted by engine operation modes, a given algorithm automatically changes a value of the minimal static response temperature of a detector, as well as value of the rate of rise in the temperature of its response. The experimental results showed that in the initial period of engine operation, the temperature change rate in the engine compartment fluctuates and is the largest. It can exceed 290 °С/min. However, regardless of the type of vehicle and the type of engine, when the temperature reaches technological, the temperature change rate would vary within small limits, approximately 30÷50 °С/min. The study results from the Simulink software package (USA) in the MATLAB programming environment (USA) confirm the effectiveness of the programmed operational algorithm of a thermal fire detector. The developed algorithm of a fire detector's operation makes it possible to detect the fire at an early stage and reduce the cases of the device's false response. The fire detector responded to both the maximal and dynamic components. As regards the maximal component, the proposed detector is triggered about 2.3 times faster than the classic maximal thermal fire detector. Detection of fire at an early stage makes it possible to quickly use the fire extinguishing system. [ABSTRACT FROM AUTHOR]

This paper proposes an algorithm for selecting the required frequency of injected current for problems of personalized multi-frequency electricalimpedance tomography. The essence of the algorithm is to calculate the rate of change in the recorded difference of potentials for the assigned range of frequencies of injected current, followed by determining the frequency after which the rate of a change in potentials is minimal. Subsequently, the injection parameters are readjusted to the chosen frequency and the complete process of electricalimpedance tomography is started. The proposed solutions were studied on four subjects with different fat mass, defined by bioimpedance analysis. Thus, it seems possible to track the dynamics of a change in the lungs of a certain patient by visualizing the reconstructed conductivity field, taking into consideration its internal features. It was established that in the course of studying lungsby using the method of electricalimpedance tomography, it is necessary to take into account the frequency of injected current at an increase in percentage of fat mass. The results of the studies showing a change in the quality of imaging the breathing process at different frequencies of injected current (from 50 kHz to 400 kHz, with a pitch of 50 kHz) are presented. For the test participants with a fat weight of 7.6 kg, 23.3 kg, 15.2 kg and 37.3 kg, the injection frequency was determined as 150 kHz, 200 kHz, 200 kHz, and 350 kHz, respectively. The proposed algorithm enables visual monitoring of lung function and can be used in the problems of pre- and postoperative monitoring of respiratory function of patients. Its use is particularly relevant for patients connected to an apparatus of artificial lung ventilation. [ABSTRACT FROM AUTHOR]

In modern conditions, due to the vastness of the territory of Kazakhstan, with a certain probability, natural disasters such as earthquakes, floods, avalanches, as well as accidents, destruction of buildings, epidemics, release of chemical toxic substances at industrial enterprises, fires in educational and medical institutions are possible, which justifies the relevance of modern methods and technologies for solving the problem of evacuation. The peculiarity of this work lies in the formation of an integrated approach for organizing the evacuation process both in peacetime as training for the event of an emergency situation (emergency), and in the event of the emergency itself. A conceptual diagram of an evacuation system is proposed that uses heterogeneous sources for receiving and transmitting information about the onset of an emergency. The input and output sources for receiving and transmitting information about the number of people in the building are determined. The main purpose of the system is to form an operational real-time evacuation plan. This work is the result of a phased implementation of an integrated evacuation system, which consists in building a mathematical model and a method for solving the problem of maximum flow in the network. A mathematical model has been developed for the optimal flow distribution along the Grindshiels network with the analysis of the flow formation and the characteristics of people’s motion in enclosed spaces. A game-theoretic approach and mathematical methods of the theory of hydraulic networks for finding an equilibrium state in flow-distribution networks have been developed. An algorithm for solving the evacuation problem using the graph approach is proposed. The results of this paper make it possible to systematically organize training evacuations, prepare resources, train the personnel responsible for evacuation in order to quickly respond in an emergency and carry out the evacuation process in order to avoid major consequences. [ABSTRACT FROM AUTHOR]

Evacuation is often the only way to save a person who is in a life-threatening situation. At present, evacuation software is used to simulate the movement of human flows, which does not always reflect the real processes of their movement. Therefore, it is a relevant task to build models for modeling the movement of human flows for different types of emergencies, different categories of human movement, and various spatial forms of their representation. Such a task arises when evacuating people from premises for various functional purposes. During evacuation, people often carry some goods. When people move carrying some goods, their horizontal projection takes a more complex shape than an ellipse or circle considered in earlier studies. Moreover, in practice, there is often a task to model the movement of people taking into consideration the maximum permissible distances between them. This paper reports the new quasi-phi functions of interaction between the ellipse and rectangle accounting for the maximum allowable distances between them. The proposed mathematical apparatus has made it possible to formalize the interaction between objects, thereby enabling the construction of a well-substantiated mathematical model, as well as the methods and algorithms for modeling the movement of people carrying some goods. The possibility to simulate the movement of people with certain objects has shown taking into consideration the maximum permissible distances between them. A test example of the movement of people along four corridors was simulated, in each of which there were 28 people subsequently merging into one flow. Given the uniform distribution of three types of cargo: «backpacks», «suitcases», and «bags on wheels», the movement slowed down by about 4 %. When half of the evacuees had «bags on wheels» that can move away from people at arm’s length, the slowdown was about 6 %. [ABSTRACT FROM AUTHOR]

Copyright of Eastern-European Journal of Enterprise Technologies is the property of PC TECHNOLOGY CENTER and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper reports a study that has established the possibility of improving the effectiveness of the method of figurative transformations in order to minimize Boolean functions on the Reed-Muller basis. Such potential prospects in the analytical method have been identified as a sequence in the procedure of inserting the same conjuncterms of polynomial functions followed by the operation of super-gluing the variables. The extension of the method of figurative transformations to the process of simplifying the functions of the polynomial basis involved the developed algebra in terms of the rules for simplifying functions in the Reed-Muller basis. It was established that the simplification of Boolean functions of the polynomial basis by a figurative transformation method is based on a flowchart with repetition, which is actually the truth table of the predefined function. This is a sufficient resource to minimize functions that makes it possible not to refer to such auxiliary objects as Karnaugh maps, Weich charts, cubes, etc. A perfect normal form of the polynomial basis functions can be represented by binary sets or a matrix that would represent the terms of the functions and the addition operation by module two for them. The experimental study has confirmed that the method of figurative transformations that employs the systems of 2-(n, b)-design, and 2-(n, x/b)-design in the first matrix improves the efficiency of minimizing Boolean functions. That also simplifies the procedure for finding a minimum function on the Reed-Muller basis. Compared to analogs, this makes it possible to enhance the performance of minimizing Boolean functions by 100–200 %. There is reason to assert the possibility of improving the efficiency of minimizing Boolean functions in the Reed- Muller basis by a method of figurative transformations. This is ensured by using more complex algorithms to simplify logical expressions involving a procedure of inserting the same function terms in the Reed-Muller basis, followed by the operation of super-gluing the variables. [ABSTRACT FROM AUTHOR]

The problem of computer diagnostics of complex systems is one of the non-trivial tasks of modern information technology. Such systems are, for example, computer networks, automatic and/or automated control systems for complex technological objects, including related to complex problems of environmental protection, biology, etc. In pattern recognition, one of the major problems is forming subspaces of informative features, which only in the «ensemble» allow diagnosing the states of such systems with a high degree of reliability. An effective approach to solving this problem based on the principles of inductive modeling of complex systems is proposed. The quality criterion for recognizing classes of patterns is formulated, which also makes it possible to evaluate the quality of the constructed ensemble of informative features. As an example, the problem of constructing an ensemble of informative features represented by a binary code based on the data of an experiment to determine the hazard levels of some plant protection products is considered. Real primary data on plant protection products used in practice were applied to recognize the effect of certain characteristics on the so-called integrated «hazard indicator». Comparative numerical estimates of the effectiveness of the proposed approach are given. In this case, there can be a fivefold gain in the amount of computations for a relatively small number of input features equal to 5 compared to the known algorithms of the class considered in the paper. It is shown that, from a practical point of view, the described algorithm has advantages over the known algorithms with brute-force search of feature subspaces in pattern recognition problems. [ABSTRACT FROM AUTHOR]

Over the last few decades, tremendous and exponential expansion in digital contents together with their applications has emerged. The Internet represents the essential leading factor for this expansion, which provides low-cost communication tools worldwide. However, the main drawback of the Internet is related to security problems. In order to provide secure communication, enormous efforts have been spent in the cryptographic field. Recently, cryptographic algorithms have become essential for increasing information safety. However, these algorithms require random keys and can be regarded as compromised when the random keys are cracked via the attackers. Therefore, it is substantial that the generation of keys should be random and hard to crack. In this paper, this is guaranteed via one of the most efficient nature-inspired algorithms emerged by inspiring the movements of stars, galaxies, and galaxy superclusters in the cosmos that can be utilized with a mathematical model (magic cube) for generating hardly cracking random number keys. In the proposed cryptographic system, the Modified Galactic Swarm Optimization (GSO) algorithm has been utilized in which every row and column of magic cube faces are randomly rotated until reaching the optimal face, and the optimal random elements are selected as optimal key from the optimal face. The generated optimized magic cube keys are used with several versions of RC6 algorithms to encrypt various secret texts. Furthermore, these generated keys are also used for encrypting images using the logical XOR operation. The obtained results of NIST tests proved that the generated keys are random and uncorrelated. Moreover, the security of the proposed cryptographic system was proved. [ABSTRACT FROM AUTHOR]

The aim of the work is to develop a method for optimal control of handling operations with heavy lift cargo on sea vessels. Based on the review of scientific research in the field of loading heavy lift cargo, priority directions for improving the automated control systems for cargo handling operations on ships have been determined. Within a scientific hypothesis, it was proposed to synchronize solutions to the problem of ship propulsion control and automated control of heavy lift onboard cranes in order to improve the accuracy of loading processes. The paper analyzes the dynamic model of the “vessel-crane-cargo” system and the criteria of optimality in the problem of ship regulation-stabilization under minimization of loading time. An inverse loading algorithm has been developed, based on the principles of the loading control optimization with limiting the choice of motion by linear displacements and turns of the vessel. When executing the inverse algorithm, restrictions associated with the minimization of heeling moments in the “vessel-crane-cargo” system and restrictions associated with the maximum and minimum boom outreach are applied. The study determined the technical feasibility of achieving invariance in the cargo stabilization system with the inverse loading algorithm on heavy lift vessels. On the basis of the proposed method, simulation modeling of the ship loading process was carried out on simulators at the Kherson State Maritime Academy. The simulation modeling has shown that the use of the inverse algorithm will reduce the time of cargo operations by 50–70 percent and, as a result, reduce the risk of emergencies when loading the ship. It was also determined that the use of the inverse algorithm is appropriate for cargo of more than 100 tons. [ABSTRACT FROM AUTHOR]

The modern industry is dominated by electric drives of the system frequency converter‒ induction motor, which employ integer-order controllers. Allowing the implementation and adjustment of fractional order controllers in the converter itself greatly expand their capabilities and, therefore, is relevant. This paper reports a procedure for the parametric synthesis of PIλDμ-controllers of fractional order, providing for the use of the desired forms of fractional order, as well as their practical implementation in the system frequency converter–induction motor. In this case, the control object is described by a transfer function of the fractional or integer order, derived on the basis of experimental results. The study results demonstrate the possibility of constructing new, as well as modernizing existing, electromechanical systems involving the fractional-order PIλDμ-controllers with an expanded range of dynamic properties that correspond to the desired forms of fractional order. The procedure for the parametric synthesis of a PIλDμ-controller has been theoretically substantiated, which was confirmed by applying the simulation and during field experiments concerning the system frequency converter–induction motor. The reported procedure is universal because it makes it possible to synthesize the PIλDμ-controller for standard forms of both the integer and fractional orders. It is clear that the range of the desired standard forms in the synthesis process can include all possible known forms, including those of fractional order. The result of this study allows us to argue that it is possible to apply the developed algorithm of actions for those engineering tasks that aim to build such systems for various industrial mechanisms. At the same time, no restrictions are imposed on the transfer function of the control object. [ABSTRACT FROM AUTHOR]

The use of a bending machine acquired a high level of importance as a consequence of increasing the level of the industry. This paper aims to develop a more accurate and precise bending machine. The proposed bending machine has achieved brilliant output products, in which three main manufacturing parameters have been examined for the production of an equilateral triangle, which are flange length, bending angle and bending radius. The main point depends on the proposed algorithm, which has been developed based on separating the process, in which the central controller is responsible mainly for controlling the sub-controller, where the sub-controllers are programmed using PID to control the entire mechanisms of feeding and bending separately and ensure that the outcomes of these mechanisms are compatible with the input data from the central controller. Ten different dimensions of an equilateral triangle design sample with ten tries for each dimension (variable flange length, fixed bending angle equals to 60 degrees and bending radius equals to 3 mm) have been selected being produced using the bending machine, and the products have been formed two times. Firstly, using the proposed bending machine, in which the proposed algorithm is applied. Secondly, using the bending machine implemented without applying the proposed algorithm. The results have been compared in terms of error rates with respect to the standard design of products designed using CAD/CAM application. An enhancement has been recorded in terms of product accuracy and precision for the parameters of flange length, bending angle and bending radius. The overall accuracy level reaches up to 98.85228 % for a product manufactured using the proposed machine by applying the proposed algorithm compared with a product made with the machine designed without the proposed algorithm [ABSTRACT FROM AUTHOR]

Proposals for further progress of video technologies, issues that need to be resolved to implement this progress and possible ways to implement them in real devices of special and general application are made. It is proposed to supplement the conventional model of the video path with a color perception model and an adaptive model of the spectral power distribution of the illuminant. Attention is paid to the end devices of the video path, which may introduce unacceptable changes in the transmitted video information, namely color. The schemes of the algorithm of adaptation to the spectral power distribution of the illuminant are presented. The possibility of universal use of the proposed algorithm in video transmission systems is considered. The algorithm of video image adaptation to the spectral power distribution of illuminants based on the selection of reference spectral power distributions with the given color coordinates is proposed. The algorithm of allocation of the spectral power distribution of the illuminant from the overall image scene is presented. Metrological support to assess the influence of the illuminant on the quality of color rendering is proposed. It is proposed to use spectral color distributions, the set of which is presented in the paper, as optical test images for testing the color rendering quality. Comparative characteristics with existing sets of spectral power distributions are presented and it is shown that they are not enough to implement the proposed algorithm. The simulation results prove the necessity and advantages of using the proposed algorithm. The image after the application of the algorithm is such if it was observed in sunlight, regardless of what type of lighting was used during shooting or observation. In addition, the presented algorithm allows adaptation to the spectral power distribution of various illuminants, such as incandescent lamps, fluorescent, LED, signal flares, and the like. [ABSTRACT FROM AUTHOR]

The study deals with the problem of identification of nonstationary parameters of a linear object which can be described by first-order Markovian model, with the help of the simplest in computational terms single-step adaptive identification algorithms - modified algorithms by Kaczmarz and Nagumo-Noda. These algorithms do not require knowledge of information on the degree of non-stationarity of the studied object. When building the model, they use the information only about one step of measurements. Modification involves the use of the regularizing addition in the algorithms to improve their computing properties and avoid division by zero. Using a Markovian model is quite effective because it makes it possible to obtain analytic estimates of the properties of algorithms. It was shown that the use of regularizing additions in identification algorithms, while improving stability of algorithms, leads to some slowdown of the process of model construction. The conditions for convergence of regularizing algorithms by Kaczmarz and Nagumo-Noda at the evaluation of stationary parameters in mean and root-mean-square and existing measurement interference were determined. The obtained estimates differ from the existing ones by higher accuracy. Despite this, they are quite general and depend both on the degree of non-stationarity of an object, and on statistical characteristics of interference. In addition, the expressions for the optimal values of the parameters of algorithms, ensuring their maximum rate of convergence under conditions of non-stationarity and the presence of Gaussian interferences, were determined. The obtained analytical expressions contain a series of unknown parameters (estimation error, degree of non-stationarity of an object, statistical characteristics of interferences). For their practical application, it is necessary to use any recurrent procedure for estimation of these unknown parameters and apply the obtained estimates to refine the parameters that are included in the algorithms. [ABSTRACT FROM AUTHOR]

This paper considers the improved method for segmenting complex structured images acquired from space observation systems based on the particle swarm algorithm. Unlike known ones, the method for segmenting complex structured images based on the particle swarm algorithm involves the following: – highlighting brightness channels in the Red-Green-Blue color space; – using a particle swarm method in the image in each channel of brightness of the RGB color space; – image segmentation is reduced to calculating the objective function, moving speed, and a new location for each swarm particle in the image in each RGB color space brightness channel. Experimental studies have been conducted on the segmentation of a complex structured image by a method based on the particle swarm algorithm. It was established that the improved segmentation method based on the particle swarm algorithm makes it possible to segment complex structured images acquired from space surveillance systems. A comparison of the quality of segmenting a complex structured image was carried out. The comparative visual analysis of well-known and improved segmentation methods indicates the following: – the improved segmentation method based on the particle swarm algorithm highlights more objects of interest (objects of military equipment); – the well-known k-means method assigns some objects of interest (especially those partially covered with snow) to the snow cover (marked in blue); – the improved segmentation method also associates some objects of interest that are almost completely covered with snow with the snow cover (marked in blue). It has been established that the improved segmentation method based on the particle swarm algorithm reduces segmentation errors of the first kind by an average of 12 % and reduces segmentation errors of the second kind by an average of 8 %. [ABSTRACT FROM AUTHOR]

This paper proposes the new hash algorithm HBC256 (Hash based on Block Cipher) based on the symmetric block cipher of the CF (Compression Function). The algorithm is based on the wipe-pipe construct, a modified version of the Merkle-Damgard construct. To transform the block cipher CF into a one-way compression function, the Davis-Meyer scheme is used, which, according to the results of research, is recognized as a strong and secure scheme for constructing hash functions based on block ciphers. The symmetric CF block cipher algorithm used consists of three transformations (Stage-1, Stage-2, and Stage-3), which include modulo two addition, circular shift, and substitution box (four-bit S-boxes). The four substitution boxes are selected from the “golden” set of S-boxes, which have ideal cryptographic properties. The HBC-256 scheme is designed to strike an effective balance between computational speed and protection against a preimage attack. The CF algorithm uses an AES like primitive as an internal transformation. The hash image was tested for randomness using the NIST (National Institute of Standards and Technology) statistical test suite, the results were examined for the presence of an avalanche effect in the CF encryption algorithm and the HBC-256 hash algorithm itself. The resistance of HBC-256 to near collisions has been practically tested. Since the classical block cipher key expansion algorithms slow down the hash function, the proposed algorithm is adapted for hardware and software implementation by applying parallel computing. A hashing algorithm was developed that has a sufficiently large freedom to select the sizes of the input blocks and the output hash digest. This will make it possible to create an almost universal hashing algorithm and use it in any cryptographic protocols and electronic digital signature algorithms [ABSTRACT FROM AUTHOR]

The object of research is image compression algorithms based on mathematical methods. The main problem with image compression is loss of quality during recovery. The approach is proposed in which the user can determine the quality of the reconstructed image itself. This is achieved due to the use of the spline interpolation method, which allows to set the compression ratio, thus controlling the quality of the decoded image. The use of the spline function for image compression makes it possible to reduce the processing time of files due to the simplicity of the mathematical model of the algorithm. Given the accuracy of the restored image, the algorithm determines the size of the compressed file, depending on the color scale. As a result of the analysis of the proposed development, the compression coefficients are shown, which show that the size of the compressed image can be smaller than the original image by 50-70 %. The decoding is performed using known spline function coefficients. The result is compared with the original file. The difference between the intensity of the points of the source and decoded images determines the quality of the restoration. An algorithm is obtained that allows one to specify the accuracy of the reconstructed image. This result depends on the weighting coefficients of the spline function, which affect the accuracy of the construction of the approximating polynomial. A feature of the proposed approach is the ability of the user to specify the accuracy and quality of the image after decoding. This is achieved due to the fact that points close in intensity value are restored with a small error. In this paper, let’s propose an approach involving the sequential extraction of blocks of points of equal intensity. For the selected blocks, an approximating polynomial is constructed based on the spline function, and the coefficients of the polynomial are transferred to a file containing information for image reconstruction. So it is possible to obtain large compression ratios by building a polynomial for blocks containing points that are close in intensity. [ABSTRACT FROM AUTHOR]

The object of research is the process of automating systems for structuring data from several sources. The subject of the research is methods and algorithms for implementing a complete system for automated and parallel processing, validation and structuring of data. One of the most problematic areas is the merging of databases with different structures and several common fields into a generalized structure. The research was aimed at developing a system to increase the efficiency of automation of big data processing. As a result of the work, optimization methods were studied, the influence of their internal parameters on the operation of algorithms was analyzed, their main advantages and disadvantages were determined, and software was developed in which the corresponding methods were implemented. An algorithm for structuring data before processing has been obtained. Data structuring is achieved by performing the «mapping» operation. Mapping can take place by indexes of already cleaned data or using a defined dictionary with a given set of keys, which allows not to care about the sequence of storing values and their possible shift. The practical significance of the developed system lies in the improvement of methods of collecting and processing information for the purpose of its further validation, cleaning and accumulation in the following categories: geographic addresses and geo-coordinates, validation and automated addition of a mobile phone number to the international format, processing of car numbers (in modern and outdated format), VIN code of the engine and car brand, validation of urls of social networks, passport data and processing of personal data. Compared to similar methods for processing large volumes of data, the possibility of splitting the input file or stream into separate parts was used, the cleaned data from which is combined at the end of the system operation. Thanks to this, it is possible to process data whose size exceeds the available volume of the device’s RAM, and the method of working with loosely structured text files in CSV format has been improved. [ABSTRACT FROM AUTHOR]

The object of the study is complex dynamic objects. The subject of the study is the decision-making process in the problems of managing complex dynamic objects. A method of assessing the state of dynamic objects using a combined swarm algorithm is proposed. The research is based on a combined swarm algorithm - for finding a solution to the state of dynamic objects with a hierarchical structure. To train the individuals of the combined swarm algorithm (CSA), evolving artificial neural networks are used, and to select the best in the combined swarm algorithm, an improved genetic algorithm is used. The originality of the method is: – in taking into account the type of uncertainty and noise of data during the operation of the combined swarm algorithm due to the use of appropriate correction factors; – in the implementation of adaptive strategies for the search for food sources due to setting appropriate search priorities; – in taking into account the presence of a predator while choosing food sources by the flock agents of the combined swarm algorithm, which allows excluding unwanted search areas; – in the additional consideration of the available computing resources of the state analysis system of complex dynamic objects while determining the maximum permissible parameters of the combined swarm algorithm; – in the possibility of changing the search area and speed of movement by separate individuals of the flock of the combined swarm algorithm; – in determining the best individuals of the flock of the combined swarm algorithm using an improved genetic algorithm; – in training knowledge bases, carried out by training the synaptic weights of the artificial neural network, the type and parameters of the membership function, the architecture of individual elements and the architecture of the artificial neural network as a whole. The method makes it possible to increase the efficiency of data processing at the level of 14–20 % by using additional improved procedures. The proposed method should be used to solve problems of evaluating complex dynamic objects. [ABSTRACT FROM AUTHOR]

Today’s management solutions depend precisely on the successful solution of optimization problems, which are discontinuous, undifferentiated and multimodal. One of the approaches to increase the efficiency of solving optimization problems is bio-inspired algorithms. The object of the study is complex dynamic objects. The subject of the study is the decision-making process in the problems of managing complex dynamic objects. A management method using a bio-inspired algorithm is proposed. The research is based on the goose algorithm – for finding a solution to the state of dynamic objects with a hierarchical structure. Evolving artificial neural networks are used to train goose agents (GA) and an advanced genetic algorithm is used to select the best ones in the combined swarm algorithm. The originality of the proposed method lies in setting GA taking into account the uncertainty of the initial data, improved global and local search procedures. Also, the originality of the study lies in determining GA food locations, which allows choosing the priority of search in a given direction. The next element in the originality of the study is the ability to determine the indicators of guard GA, which allows adjusting the amount of time during which the GA flock will be located. Another original element of the study is the determination of the initial velocity of each GA. This makes it possible to optimize the speed of conducting exploration by each GA in a certain research direction. The method allows increasing the efficiency of data processing at the level of 10–12 % by using additional improved procedures. The proposed method should be used to solve problems of evaluating complex dynamic objects. [ABSTRACT FROM AUTHOR]

The object of study is the recognition and identification of various objects in aerospace images. To solve the problems of compressing hyperspectral aerospace images with losses, the development of a compression algorithm is proposed. As a result, an algorithm has been developed for compressing aerospace images for subsequent recognition and identification of various objects using wavelet transform for processing high- and medium-resolution space images when monitoring from remote sensing satellites, based on the use of structural features of object images. In particular, orthogonal and wavelet transforms are presented, adapted for compression of hyperspectral aerospace images with losses, an adaptive discrete cosine transform algorithm is presented, followed by quantization with a loss level and compression. Thanks to a series of experiments on hyperspectral aerospace images, the effectiveness of the proposed algorithm in terms of the degree of compression, as well as the characteristics of the limits of its applicability, can be highlighted. The use of wavelets provides progressive compression of the bitstream, which makes it possible to achieve lossless compression with minimal loss of information due to the modified Huffman algorithm with a compression ratio of 9 more than 2.5 times in existing algorithms, as well as the quality metric of the restored images, the peak signalto-noise ratio is sufficiently below 32.56. The developed compression algorithm demonstrates the effectiveness of its application in terms of a set of characteristics and is superior to analogues. The scope and conditions for the practical use of the results obtained is a comparison of the proposed algorithm with the results of experiments obtained for universal compression algorithms for archivers and a compressor. [ABSTRACT FROM AUTHOR]

Copyright of Eastern-European Journal of Enterprise Technologies is the property of PC TECHNOLOGY CENTER and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The main attention is paid to the analysis of electromyogram (EMG) signals using Poincaré plots (PP). It was established that the shapes of the plots are related to the diagnoses of patients. To study the fractal dimensionality of the PP, the method of counting the coverage figures was used. The PP filtration was carried out with the help of Haar wavelets. The self-similarity of Poincaré plots for the studied electromyograms was established, and the law of scaling was used in a fairly wide range of coverage figures. Thus, the entire Poincaré plot is statistically similar to its own parts. The fractal dimensionalities of the PP of the studied electromyograms belong to the range from 1.36 to 1.48. This, as well as the values of indicators of Hurst exponent of Poincaré plots for electromyograms that exceed the critical value of 0.5, indicate the relative stability of sequences. The algorithm of the filtration method proposed in this research involves only two simple stages: 1. Conversion of the input data matrix for the PP using the Jacobi rotation. 2. Decimation of both columns of the resulting matrix (the so-called "lazy wavelet-transformation", or double downsampling). The algorithm is simple to program and requires less machine time than existing filters for the PP. Filtered Poincaré plots have several advantages over unfiltered ones. They do not contain extra points, allow direct visualization of short-term and long-term variability of a signal. In addition, filtered PPs retain both the shape of their prototypes and their fractal dimensionality and variability descriptors. The detected features of electromyograms of healthy patients with characteristic low-frequency signal fluctuations can be used to make clinical decisions [ABSTRACT FROM AUTHOR]

The object of research is digital signatures. The Falcon digital signature scheme is one of the finalists in the NIST post-quantum cryptography competition. Its distinctive feature is the use of floating-point arithmetic. However, floating-point arithmetic has so-called rounding noise, which accumulates during computations and in some cases may lead to significant changes in the processed values. The work considers the problem of using rounding noise to build attacks on implementation. The main result of the study is a novel attack on implementation, which enables the secret key recovery. This attack differs from existing attacks in using two separately secure implementations with different computation orders. As a result of the analysis, the conditions under which secret key recovery is possible were revealed. The attack requires 300,000 signatures and two implementations to recover key. The probability of successful attack ranges from 70 % to 76 %. This probability is explained by the structure of the Gaussian sampling algorithm used in the Falcon digital signature. At the same time, a necessary condition for conducting an attack is identical seed during signature generation. This condition makes the attack more theoretical than practical since the correct implementation of the Falcon makes probability of two identical seeds negligible. However, the possible usage of floating-point noise shows potential existence of additional attack vectors for the Falcon that should be covered in security models. The results could be used in the construction of digital signature security models and their implementation in existing information and communication systems. [ABSTRACT FROM AUTHOR]

The object of the study is decision support systems. The subject of the study is the decision-making process in management problems using a combined bio-inspired algorithm, consisting of: – the improved wolf optimization algorithm and the improved sparrow search algorithm – for solving optimization problems regarding the object state; – an advanced genetic algorithm – for selecting the best agents in flocks; – an advanced training method – for deep training of agents to improve the optimization characteristics of agents. A solution search method using an improved bio-inspired algorithm is proposed. The method has the following sequence of actions: – input of initial data; – initialization of the search for a flock of sparrows and its parameters; – ranking and selection of sparrow agents using an advanced genetic algorithm; – updating the sparrow location for the discoverer; – checking the conditions for updating the position of sparrows; – initialization of additional search parameters; – running the gray wolf optimization algorithm; – training agents’ knowledge bases; – determining the amount of necessary computing resources of the intelligent decision support system. The originality of the proposed method lies in the combined use of bio-inspired algorithms, setting agents taking into account the uncertainty of the initial data, advanced global and local search procedures. The method makes it possible to increase the efficiency of data processing at the level of 19 % using additional improved procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic processes in the interest of solving national security problems. [ABSTRACT FROM AUTHOR]