DOI: 10.7256/2454-0714.2019.3.30341

Abstract: The subject of the study is the heat exchange devices using the additive technology method. For the introduction of additive technologies in the production of heat exchange devices of electronic equipment, the main stages of printing metal products on a 3D printer were determined. Due to the lack of general theoretical ideas about the orientation of the synthesized product in the camera of a 3D printer, twelve classes of overhanging surfaces are identified. In order to simplify the calculation of the volume of supports for overhanging surfaces, it is proposed to use the projection of the part at six basic positions. In general, the process of selecting the best option for basing a part based on the minimum amount of supports is presented from the following steps: selecting six basic positions; calculation of the area and height of overhanging surfaces for each base; calculation of the volume of supports for each base; comparison of the received data. As a result of the research, a general scheme was developed for the production of heat exchangers using additive technologies. When solving a scientific problem, theoretical research methods were used, based on: decomposition of problems, system analysis, methods of analytical geometry. The main conclusions of the study are the development of a methodological apparatus for automating the design of the geometric shape of heat exchangers using additive technology, based on the classification of overhanging surfaces according to geometric signs and the method of basing the product, aimed at minimizing the volume of supports. This allowed us to create algorithms that, in turn, can be grouped and translated into technological regulations for specialists in preparation for the production of complex products, both in pilot and mass production.

DOI: 10.7256/2454-0714.2019.3.30502

Abstract: The object of research is the process of choosing the optimal hardware architecture for organizing resource-intensive computing. The subject of the research is the process of solving optimization problems by genetic algorithms on GPU and CPU architectures. The influence of the choice of hardware architecture on the process of solving the optimization problem is shown: the absolute and relative dependences of the slowdown of the computing process, when choosing an irrational hardware architecture, on the number of individuals processed by the algorithm are determined. It is established that for the considered problem, the boundary of the most efficient hardware configuration can be in the range from 1000 to 5000 individuals. For this reason, it is advisable to describe the blurring of the boundary of an effective hardware configuration as a set of pairs “number of individuals — membership in a transition”. The research method is based on an analysis of the results of a computational experiment. The purpose of the experiment is to determine the dependencies of the runtime of the genetic algorithm on the GPU and CPU architectures on the number of individuals generated (chromosomes). The dependences of the minimum and maximum time of the genetic algorithm running on the GPU and CPU on the number of individuals are compared. It is shown that when solving the considered problem, the minimum and maximum time dependences of the algorithm performed on the GPU are close to a linear function; the minimum time dependences of the algorithm performed on CPU are close to a linear function, and the maximum to polynomial.

DOI: 10.7256/2454-0714.2019.3.30646

Abstract: The article presents the results of determining the moisture-binding ability and plasticity of food products. Many indicators depend on the ability of meat and fish to bind moisture, including juiciness, tenderness, yield, loss during heat treatment, and appearance. The objects for research were Baikal omul, fresh and salted, beef meat in thawed condition. The moisture-binding ability and plasticity of the objects of study were evaluated by the pressing method. The paper presents the calculations performed using the traditional method and the method of digital processing of color images. Digital image processing was performed using a program developed by the authors, the article provides drawings and tables obtained during image processing. The undoubted advantage of the processing program compared to the traditional method is a significant reduction in time for processing images and the ability to process a large amount of data in a short time. When creating the necessary shooting conditions, the digital image processing method for determining the moisture-binding ability and plasticity of food products can be successfully used for laboratory research in determining the quality of meat and fish products.

DOI: 10.7256/2454-0714.2019.3.30583

Abstract: The subject of the research is the concept of creating intelligent information protection systems based on neural network intrusion detection systems in automated data processing systems, developed as part of the funded project of the RFBR No. 19-01-00383. The object of the study is the intelligent information protection systems in automated data processing systems, built on the basis of neural intrusion detection systems, and later on the mechanisms of artificial immune systems. The authors consider adaptability, learning ability and controllability as the main conceptual requirements for the intrusion detection systems. Particular attention is focused on the construction of a flexible intelligent information protection system containing intrusion detection systems in both the nodes of the structural components of automated data processing systems, and in data transmission networks between structural components. Methodological studies of the chosen research direction are carried out using the methods of artificial intelligence, system analysis, the theory of intelligent information systems in the field of artificial intelligence. The work uses the achievements of a system-conceptual approach to information protection in automated data processing systems. The main result of the study is the conclusion that successful protection of information in automated data processing systems can only be carried out in a network in the form of interconnected local intrusion detection systems using neural network technologies combined into a single head center based on a system-conceptual approach. To combat unauthorized intrusions, it is necessary to adopt a unified systematic approach based on uniform legal, organizational and technical measures to protect information. The application of a system-conceptual approach to the creation of intrusion detection systems based on neural network technologies will contribute to the development of new tools, methods and activities for the intelligent management of information security in automated data processing systems.

DOI: 10.7256/2454-0714.2019.3.30393

Abstract: In this paper, the author considers the problem of applying prediction in classical and parallel programming of mathematical modeling problems based on the numerical integration of partial differential equations. Prediction can be used to replace fragments of a mathematical model with simpler approximate relations, to anticipate the values received during parallel counting, to predict the execution time of fragments of a parallel program when deciding whether to use a sequential or parallel algorithm and when balancing the load of individual processors of a computing system. To formalize the types of predictors and determine the mathematical relationships that allow them to be calculated, the approaches and methods of computational mathematics (theory of interpolation and extrapolation) are used. To determine the software implementations of predictors, approaches that are characteristic of parallel programming engineering are used. The results are verified experimentally. For the first time, a new type of technological means of prediction for use in parallel programming is proposed - prediction-solving channels. Two types of channels are proposed - autoregressive point and linear (explicit or implicit) collective solutions. The mathematical aspects of prediction in such channels are described, basic programming tools are briefly described. It is shown that combining channels with data prediction tools simplifies the programming of a number of algorithms related to numerical modeling, and allows, in particular, hidden transitions from explicit difference schemes to implicit ones, which are more stable in counting, as well as from sequential counting algorithms to parallel ones. Using the example of the problem of numerical integration of the non-stationary heat equation, it is shown that the adequate use of channels in some cases allows you to speed up the calculation on multi-core computing systems.

DOI: 10.7256/2454-0714.2019.3.30637

Abstract: The object of study is shaping of the curve of the line on a discrete set of source data. In this case, a discrete series of points-nodes with tangents in them and the value of the curvature of the first segment in its initial node are taken as initial data. The subject of the study is a fractional rational Bezier curve of the second order. The authors investigate in detail the aspects of obtaining segments of rational Bezier curves in the direction of docking their C2 smoothness in order to obtain a Bezier spline.A mathematical method is applied based on the analytical representation of fractional rational Bezier segments of the second order using the apparatus of mathematical analysis and differential calculus. The novelty of the study lies in the fact that the obtained mathematical model of the spline allows you to directly indicate in the process of shaping the types of segments that make it up: parabolic, elliptical or hyperbolic. It is shown that the standard form of the Bezier curve representation can be reduced to a simpler form. This proposed model is qualitatively different from existing models. Numerical examples of obtaining open and closed Bezier spline are considered.

DOI: 10.7256/2454-0714.2019.3.30474

Abstract: The object of study is the geometric model of the incremental molding process of parts from sheet material.The subject of the study is a graphical model for finding the optimal values of the parameters of the molding process based on multidimensional descriptive geometry. The author in the article examined the main optimizing factors and process parameters. Particular attention is paid to the problems of constructing geometric models for determining optimizing factors (contact zone, processing time and surface quality of the resulting part) and parameter optimization (profile and trajectory of the shaping tool) for incremental shaping.The research method is a method of constructing a graphical optimization model of the process using the projection drawing of Radishchev for multidimensional space. Mathematical modeling was also applied to verify the correctness of the obtained optimal parameters. The novelty of the study lies in the application of multidimensional descriptive geometry methods for a multifactor, multicomponent system in the study of the incremental molding process in order to improve the quality of manufactured parts. Main conclusions. Using a graphical optimization model based on multidimensional descriptive geometry, a range of values of incremental molding parameters was obtained for a product of predicted quality. The process was simulated with the obtained parameters. An incremental molding of a conical-shaped sheet metal part was carried out. The results obtained correspond to the specified quality criteria.

DOI: 10.7256/2454-0714.2019.3.30541

Abstract: The problem of synthesis of search algorithms for a set of inverse-segment sequences with a given period is considered. Inverse-segment sequences are pseudorandom sequences having the likelihood of the occurrence of symbols 0 and 1 and the variety of their autocorrelation functions. In hardware implementation, the most widely used are inverse-segment sequences formed by pseudorandom sequence generators based on an n-bit shift register with linear feedbacks. To use inverse-segment sequences in applied problems, as well as further study of their properties, it is necessary to solve the problem of finding a set of inverse-segment sequences with a given period, and the number of disjoint sequences increases significantly with increasing n. A number of basic approaches to the synthesis of inverse-segment sequence search algorithms are considered, and the analysis of the obtained algorithms, their algorithmic complexity, and memory consumption are carried out. Inverse segment sequences are of practical interest due to the equiprobability of the occurrence of symbols 0 and 1 and the variety of their autocorrelation functions. A number of algorithms for finding inverse-segment sequences with a given period, with the principle of enumerating the initial states of the shift register at the base, are investigated. All the considered algorithms use an abbreviated method of storing inverse segment sequences in various data structures using the number of one-to-one given inverse segment sequences. Studied their algorithmic complexity and memory consumption. Recommendations have been made for choosing an algorithm for searching inverse-segment sequences and the synthesis of new algorithms.