Pub Date : 2022-05-31DOI: 10.37791/2687-0649-2022-17-3-34-44
O. Nepomnyashchiy
The problems of high-level synthesis of very large integrated circuits (VLSI) are considered. The review of the subject area shows that the use of the imperative model and corresponding programming languages does not provide efficient parallelization of algorithms and the possibility of efficient parallelization of programs. This leads to the impossibility of providing the required technical characteristics. This is due to the specifics of VLSI, which is essentially a scheme of parallel processing of information flows. An original VLSI synthesis method is presented. The method based on the functional-streaming paradigm of parallel computing. This method allows ensuring architectural independence and maximum coverage of implementation options. The route map of VLSI functional-flow method is outlined. The problem of estimating the requested hardware resources and clock frequency, necessary for solving, is formulated. This problem must be solved at the early stages of design. A method for estimating resources in the process of functional-flow synthesis is proposed. The method is based on the use of an additional meta-layer (HDL-graph). Taking into account the polymorphism of the solution of the resource estimation problem, it is proposed to use machine learning technologies in the new method. It is shown that the application of the indicated method in the synthesis process makes it possible to provide the most accurate assessment of resources. This is possible, because the HDL graph is a data flow graph typed and structured in accordance with the functional-flow model of parallel computing. Machine learning allows to most effectively obtain a solution to the problem of optimal selection of the required resources. The classes of resources for which an assessment is required are highlighted. Selected parameters for building a resource assessment model. The software implementation and comparison of the proposed resource estimation method based on linear regression models, neural networks and gradient boosting with known approaches is performed. It is shown that when using the technology of functional-flow synthesis when applying the proposed method for estimating the required resources and performance, an increase in the accuracy of the estimate at the high-level stage.
{"title":"Resource estimation method in the process of functional-flow high-level VLSI synthesis","authors":"O. Nepomnyashchiy","doi":"10.37791/2687-0649-2022-17-3-34-44","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-3-34-44","url":null,"abstract":"The problems of high-level synthesis of very large integrated circuits (VLSI) are considered. The review of the subject area shows that the use of the imperative model and corresponding programming languages does not provide efficient parallelization of algorithms and the possibility of efficient parallelization of programs. This leads to the impossibility of providing the required technical characteristics. This is due to the specifics of VLSI, which is essentially a scheme of parallel processing of information flows. An original VLSI synthesis method is presented. The method based on the functional-streaming paradigm of parallel computing. This method allows ensuring architectural independence and maximum coverage of implementation options. The route map of VLSI functional-flow method is outlined. The problem of estimating the requested hardware resources and clock frequency, necessary for solving, is formulated. This problem must be solved at the early stages of design. A method for estimating resources in the process of functional-flow synthesis is proposed. The method is based on the use of an additional meta-layer (HDL-graph). Taking into account the polymorphism of the solution of the resource estimation problem, it is proposed to use machine learning technologies in the new method. It is shown that the application of the indicated method in the synthesis process makes it possible to provide the most accurate assessment of resources. This is possible, because the HDL graph is a data flow graph typed and structured in accordance with the functional-flow model of parallel computing. Machine learning allows to most effectively obtain a solution to the problem of optimal selection of the required resources. The classes of resources for which an assessment is required are highlighted. Selected parameters for building a resource assessment model. The software implementation and comparison of the proposed resource estimation method based on linear regression models, neural networks and gradient boosting with known approaches is performed. It is shown that when using the technology of functional-flow synthesis when applying the proposed method for estimating the required resources and performance, an increase in the accuracy of the estimate at the high-level stage.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"9 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78022237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-31DOI: 10.37791/2687-0649-2022-17-3-16-33
O. Stoianova, Valeriia D. Moskaleva
Research and development (R&D) ensure stable functioning and forms the innovative potential of most companies in the production sector. Ineffective R&D management leads to the fact that many initiated projects go beyond planned deadlines and budgets, and much of the intermediate R&D results are not completed. The complexity of R&D management is associated with high information uncertainty regarding the performance of R&D and the productivity of employees. The paper considers a multi-model method of decision support for R&D management in companies. To reduce information uncertainty in solving various management problems it is proposed to use an ontological model of intellectual capital of the company, simulation models of R&D processes and individual stages, fuzzy logic models to obtain integral assessments of management decisions. The method provides a basis for making decisions on the possibility and expediency of using previously obtained R&D results (scientific and technological reserve); on the feasibility of the proposed project based on the assessment of its feasibility; on the project organization (volume-calendar planning); on the allocation of resources to tasks; on the incentives for performers; on the planning of activities for additional training and organization of information support. The paper provides a general description of the method, as well as an example of its use to support decision-making on the feasibility of an R&D project based on its assessment. Two structures for organizing the R&D process in a manufacturing company are considered as alternatives. After selecting the best structure, the impact of staffing quality on the integral feasibility assessment is evaluated.
{"title":"The multi-model decision support method for R&D management","authors":"O. Stoianova, Valeriia D. Moskaleva","doi":"10.37791/2687-0649-2022-17-3-16-33","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-3-16-33","url":null,"abstract":"Research and development (R&D) ensure stable functioning and forms the innovative potential of most companies in the production sector. Ineffective R&D management leads to the fact that many initiated projects go beyond planned deadlines and budgets, and much of the intermediate R&D results are not completed. The complexity of R&D management is associated with high information uncertainty regarding the performance of R&D and the productivity of employees. The paper considers a multi-model method of decision support for R&D management in companies. To reduce information uncertainty in solving various management problems it is proposed to use an ontological model of intellectual capital of the company, simulation models of R&D processes and individual stages, fuzzy logic models to obtain integral assessments of management decisions. The method provides a basis for making decisions on the possibility and expediency of using previously obtained R&D results (scientific and technological reserve); on the feasibility of the proposed project based on the assessment of its feasibility; on the project organization (volume-calendar planning); on the allocation of resources to tasks; on the incentives for performers; on the planning of activities for additional training and organization of information support. The paper provides a general description of the method, as well as an example of its use to support decision-making on the feasibility of an R&D project based on its assessment. Two structures for organizing the R&D process in a manufacturing company are considered as alternatives. After selecting the best structure, the impact of staffing quality on the integral feasibility assessment is evaluated.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"8 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75629155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-31DOI: 10.37791/2687-0649-2022-17-3-97-104
R. Y. Golikov
This paper considers the actual problem of graphical information converting back into raw data format that was used to represent it. This is due to the great scientifi achievements contained in editions from the Soviet period, as well as the intention global publishers from "unfriendly" countries to close access for Russian and Belarusian organisations to scientific publications and technical information databases. As a result, Russian scientists can only have graphical materials in formats similar to PDF documents. This paper considers a fairly simple way of solving this problem when digitising graphs in printed or electronic publications with low resolution and a large picture scale, which does not allow to detail its separate fragments. The procedure for pre-processing the original image in bitmap format is described. In order to improve the numerical data resulting accuracy from the subsequent digitising, a number of features are recommended, which are available in the well-known and most common graphical editors. These functions include changing the color mode of the image, color inversion, sharpening and contrast, linear scaling (vertical and horizontal scaling), and graph line spline approximation. The above operations are accessible to users with the minimum familiarity of graphical editors Microsoft Power Point and Adobe Photoshop. As an developed procedure use example, the results of FRB 160317 signal digitising (a so-called Fast Radio Burst), are presented. The digitising of its graphical image has provided more accurate additional information on signal characteristics not given by publication authors. A visual evaluation of the digitised FRB 160317 signal accuracy by matching it with the original graphical image is presented, which showed a satisfactory match to the original. The numerical data array obtained by digitising the raw graphical material using a pre-processing procedure is becomes available for further analysis. The described way can be used by university teachers both at the initial stages of students teaching to work with images and carry out data analysis, and when preparing teaching materials when organising the educational process using distance learning technologies. The results are applicable at the starting stages of scientifi research in the initial data set formation for dependency analysis in various subject areas, where there are no initial samples refl the results of observation.
本文考虑了将图形信息转换回用于表示图形信息的原始数据格式的实际问题。这是由于苏联时期的版本中包含了巨大的科学成就，以及来自“不友好”国家的全球出版商意图关闭俄罗斯和白俄罗斯组织对科学出版物和技术信息数据库的访问。因此，俄罗斯科学家只能拥有类似PDF文件格式的图形材料。本文考虑了一种相当简单的方法来解决这个问题，当数字图形印刷或电子出版物低分辨率和大的图片规模，不允许详细说明其单独的片段。描述了以位图格式对原始图像进行预处理的程序。为了提高随后数字化产生的数值数据的准确性，推荐了许多功能，这些功能可在知名和最常见的图形编辑器中使用。这些功能包括改变图像的颜色模式，颜色反转，锐化和对比度，线性缩放(垂直和水平缩放)和图形样条近似。以上操作对于熟悉图形编辑器Microsoft Power Point和Adobe Photoshop的用户来说都是可以实现的。作为一个开发的程序应用实例，介绍了FRB 160317信号数字化(所谓的快速射电暴)的结果。其图形图像的数字化提供了更准确的附加信息的信号特征，而不是由出版物的作者。通过与原始图形图像的匹配，对数字化后的FRB 160317信号精度进行了视觉评价，结果表明与原始图像匹配良好。通过使用预处理程序将原始图形材料数字化获得的数值数据阵列可用于进一步分析。所描述的方法可以被大学教师在学生教学的初始阶段使用图像和进行数据分析，以及在使用远程学习技术组织教育过程时准备教材时使用。该结果适用于在科学研究的起始阶段，在没有初始样本的情况下，对各个学科领域进行依赖分析的初始数据集形成。
{"title":"A way to improve the quality of graphical data digitising","authors":"R. Y. Golikov","doi":"10.37791/2687-0649-2022-17-3-97-104","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-3-97-104","url":null,"abstract":"This paper considers the actual problem of graphical information converting back into raw data format that was used to represent it. This is due to the great scientifi achievements contained in editions from the Soviet period, as well as the intention global publishers from \"unfriendly\" countries to close access for Russian and Belarusian organisations to scientific publications and technical information databases. As a result, Russian scientists can only have graphical materials in formats similar to PDF documents. This paper considers a fairly simple way of solving this problem when digitising graphs in printed or electronic publications with low resolution and a large picture scale, which does not allow to detail its separate fragments. The procedure for pre-processing the original image in bitmap format is described. In order to improve the numerical data resulting accuracy from the subsequent digitising, a number of features are recommended, which are available in the well-known and most common graphical editors. These functions include changing the color mode of the image, color inversion, sharpening and contrast, linear scaling (vertical and horizontal scaling), and graph line spline approximation. The above operations are accessible to users with the minimum familiarity of graphical editors Microsoft Power Point and Adobe Photoshop. As an developed procedure use example, the results of FRB 160317 signal digitising (a so-called Fast Radio Burst), are presented. The digitising of its graphical image has provided more accurate additional information on signal characteristics not given by publication authors. A visual evaluation of the digitised FRB 160317 signal accuracy by matching it with the original graphical image is presented, which showed a satisfactory match to the original. The numerical data array obtained by digitising the raw graphical material using a pre-processing procedure is becomes available for further analysis. The described way can be used by university teachers both at the initial stages of students teaching to work with images and carry out data analysis, and when preparing teaching materials when organising the educational process using distance learning technologies. The results are applicable at the starting stages of scientifi research in the initial data set formation for dependency analysis in various subject areas, where there are no initial samples refl the results of observation.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"83 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74554482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-31DOI: 10.37791/2687-0649-2022-17-3-55-72
Yury N. Lavrenkov
The work presents analysis of possible application of self-generating neural networks, which can independently generate a topological map of neuron connections while modelling biological neurogenesis, in multi-threaded information communication systems. A basic optical neural network cell is designed on the basis of the applied layered composition performing data processing. A map of neuron connections represents not an ordered structure providing a regular graph for exchange of information between neurons, but a set of cognitive reserve represented as an unconnected set of neuromorphic cells. Modelling of neuron death (apoptosis) and creation of dendrite-axon connections makes it possible to implement a stepwise neural network growth algorithm. Despite challenges in implementing this process, creating a growing network in an optical neural network framework solves the problem of initial forming of the neural network architecture, which greatly simplifies the learning process. Neural network cells used with the network growth algorithm resulted in neural network structures that use internal self-sustaining rhythmic activity to process information. This activity is a result of spontaneously formed closed neural circuits with common neurons among neuronal cells. Such organisation of recirculation memory leads to solutions with reference to such intra-network activity. As a result, response of the network is determined not only by stimuli, but also by the internal state of the network and its rhythmic activity. Network functioning is affected by internal rhythms, which depend on the information passing through the neuron clusters, which results in formation of a specific rhythmic memory. This can be used for tasks that require solutions to be worked out based on certain parameters, but they shall be unreproducible when the network is repeatedly stimulated by the same influences. Such tasks include ensuring information transmission security when using some set of carriers. The task of determining a number of frequencies and their frequency plan depends on external factors. To exclude possible repeating generation of the same carrier allocation, it is necessary to use networks of the configuration under consideration that can influence generation of solutions through the gathered experience.
{"title":"Synthesis of an optical neuromorphic structure with differentiated artificial neurons for information flow distribution","authors":"Yury N. Lavrenkov","doi":"10.37791/2687-0649-2022-17-3-55-72","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-3-55-72","url":null,"abstract":"The work presents analysis of possible application of self-generating neural networks, which can independently generate a topological map of neuron connections while modelling biological neurogenesis, in multi-threaded information communication systems. A basic optical neural network cell is designed on the basis of the applied layered composition performing data processing. A map of neuron connections represents not an ordered structure providing a regular graph for exchange of information between neurons, but a set of cognitive reserve represented as an unconnected set of neuromorphic cells. Modelling of neuron death (apoptosis) and creation of dendrite-axon connections makes it possible to implement a stepwise neural network growth algorithm. Despite challenges in implementing this process, creating a growing network in an optical neural network framework solves the problem of initial forming of the neural network architecture, which greatly simplifies the learning process. Neural network cells used with the network growth algorithm resulted in neural network structures that use internal self-sustaining rhythmic activity to process information. This activity is a result of spontaneously formed closed neural circuits with common neurons among neuronal cells. Such organisation of recirculation memory leads to solutions with reference to such intra-network activity. As a result, response of the network is determined not only by stimuli, but also by the internal state of the network and its rhythmic activity. Network functioning is affected by internal rhythms, which depend on the information passing through the neuron clusters, which results in formation of a specific rhythmic memory. This can be used for tasks that require solutions to be worked out based on certain parameters, but they shall be unreproducible when the network is repeatedly stimulated by the same influences. Such tasks include ensuring information transmission security when using some set of carriers. The task of determining a number of frequencies and their frequency plan depends on external factors. To exclude possible repeating generation of the same carrier allocation, it is necessary to use networks of the configuration under consideration that can influence generation of solutions through the gathered experience.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"51 5","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72466779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-31DOI: 10.37791/2687-0649-2022-17-3-117-130
A. Blinov, Borisov Andrey V., L. Konchina, Kseniia S. Maslova, K. D. Filippenkov
The objective of the study is the development of 3D variable-length link model with electric drives to be used in designing of next-generation comfortable exoskeletons. The developed link model has two inertial absolutely rigid sections on its ends and a variable- length section, considered weightless, in between. The mechanical part of the variable-length link model has been implemented in the universal computer math "Wolfram Mathematcia 11.3" environment by building the system of Lagrange – Maxwell differential equations. The electro-mechanical link model with electric drives has been implemented in the MatLab Simulink environment. The implemented model includes the following units: the trajectory synthesis unit per each degree of freedom, the unit for controlling torques calculation based on differential equations of motion, the unit for selecting electric motors with gears, the unit for calculating electric current per each motor and implementing the control system. The electric motors, reducers, rack and pinion gears implementing the specified and programmed link motion have been selected. The inertial and geometrical variable-length link parameters corresponding to the human tibia in the period of the single-support step phase have been selected. The drives implementing the link rotation are situated in the bottom link point in the combination of two orthogonal cylindrical hinges. One of these hinges is fixed to the supporting surface, the other one is fixed to the link end. This hinge combination simulates human ankle joint in the single-support step phase. The drive controlling the link length change is situated at the end of the bottom absolutely rigid weighty link section. The programmed trajectories for generalized coordinates are specified based on the simulation requirements of the anthropomorphic tibia motion. As a result, the electro-mechanical model of a variable- length link with parameters corresponding to the average man’s tibia has been developed. The drives and gears that allow implementing the motion close to anthropomorphic one have been selected. The implementation of this motion based on the developed software in the computer math "Wolfram Mathematica 11.3" environment and in the MatLab Simulink system has been demonstrated. The numerical calculations are presented.
{"title":"Modeling the dynamics of an exoskeleton link of variable length using the Lagrange – Maxwell system of differential equations of motion","authors":"A. Blinov, Borisov Andrey V., L. Konchina, Kseniia S. Maslova, K. D. Filippenkov","doi":"10.37791/2687-0649-2022-17-3-117-130","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-3-117-130","url":null,"abstract":"The objective of the study is the development of 3D variable-length link model with electric drives to be used in designing of next-generation comfortable exoskeletons. The developed link model has two inertial absolutely rigid sections on its ends and a variable- length section, considered weightless, in between. The mechanical part of the variable-length link model has been implemented in the universal computer math \"Wolfram Mathematcia 11.3\" environment by building the system of Lagrange – Maxwell differential equations. The electro-mechanical link model with electric drives has been implemented in the MatLab Simulink environment. The implemented model includes the following units: the trajectory synthesis unit per each degree of freedom, the unit for controlling torques calculation based on differential equations of motion, the unit for selecting electric motors with gears, the unit for calculating electric current per each motor and implementing the control system. The electric motors, reducers, rack and pinion gears implementing the specified and programmed link motion have been selected. The inertial and geometrical variable-length link parameters corresponding to the human tibia in the period of the single-support step phase have been selected. The drives implementing the link rotation are situated in the bottom link point in the combination of two orthogonal cylindrical hinges. One of these hinges is fixed to the supporting surface, the other one is fixed to the link end. This hinge combination simulates human ankle joint in the single-support step phase. The drive controlling the link length change is situated at the end of the bottom absolutely rigid weighty link section. The programmed trajectories for generalized coordinates are specified based on the simulation requirements of the anthropomorphic tibia motion. As a result, the electro-mechanical model of a variable- length link with parameters corresponding to the average man’s tibia has been developed. The drives and gears that allow implementing the motion close to anthropomorphic one have been selected. The implementation of this motion based on the developed software in the computer math \"Wolfram Mathematica 11.3\" environment and in the MatLab Simulink system has been demonstrated. The numerical calculations are presented.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"10 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79231853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-31DOI: 10.37791/2687-0649-2022-17-3-45-54
A. E. Trubin, V. Ozheredov, A. Morozov, A. V. Batishchev, A. N. Aleksahin, E. Filimonova
In this article, the construction and analysis of machine learning models were performed for short-term forecasting in the cryptocurrency market on the example of bitcoin – one of the most popular cryptocurrencies in the world. The initial data for the study leads to the conclusion that over the long period of its existence, bitcoin has shown a high degree of volatility, especially evident in comparison with traditional financial instruments. The article substantiates that this market is influenced by a multitude of factors. No one can say for sure what makes up the value of a particular cryptocurrency, as it involves a range of reasons, which cannot be fully taken into account. To overcome this problem, we have considered the principle of recurrent neural network. It is described why networks with memory are better at making predictions on the time series than conventional autoregressive model and standard forward propagation networks. The initial data processing algorithm and transformation methods are defined. The sample was reduced in order to increase the speed of the network, by reducing the number of recalculations of weights. The algorithm of the family of recurrent neural networks was built and trained to test the hypothesis about their better adaptivity due to short-term and long-term memory. The model is evaluated on the test data representing the bitcoin exchange rate for 2021–2022, since this period is characterized by high volatility. It is concluded that it is reasonable to use a similar type of models for short-term forecasting of cryptocurrency rates.
{"title":"Building and analyzing a machine learning model for short-term bitcoin market forecasting based on recurrent neural networks","authors":"A. E. Trubin, V. Ozheredov, A. Morozov, A. V. Batishchev, A. N. Aleksahin, E. Filimonova","doi":"10.37791/2687-0649-2022-17-3-45-54","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-3-45-54","url":null,"abstract":"In this article, the construction and analysis of machine learning models were performed for short-term forecasting in the cryptocurrency market on the example of bitcoin – one of the most popular cryptocurrencies in the world. The initial data for the study leads to the conclusion that over the long period of its existence, bitcoin has shown a high degree of volatility, especially evident in comparison with traditional financial instruments. The article substantiates that this market is influenced by a multitude of factors. No one can say for sure what makes up the value of a particular cryptocurrency, as it involves a range of reasons, which cannot be fully taken into account. To overcome this problem, we have considered the principle of recurrent neural network. It is described why networks with memory are better at making predictions on the time series than conventional autoregressive model and standard forward propagation networks. The initial data processing algorithm and transformation methods are defined. The sample was reduced in order to increase the speed of the network, by reducing the number of recalculations of weights. The algorithm of the family of recurrent neural networks was built and trained to test the hypothesis about their better adaptivity due to short-term and long-term memory. The model is evaluated on the test data representing the bitcoin exchange rate for 2021–2022, since this period is characterized by high volatility. It is concluded that it is reasonable to use a similar type of models for short-term forecasting of cryptocurrency rates.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"73 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79439361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-31DOI: 10.37791/2687-0649-2022-17-3-84-96
V. Chekanin, A. Chekanin
The article deals with the problem of packing objects of arbitrary geometry. Modern methods of designing irregular packing schemes use a mathematical model based on phi-functions and a hodograph vector function of dense placement. These methods make it possible to obtain exact solutions, but they are time-consuming and very sensitive to the dimension of the problem being solved and the degree of detail of the geometry of vector objects. The use of a discrete representation of placed objects in the form of orthogonal polyhedra can signifi increase the speed of construction a packing, which makes the problem of adequately transforming the shape of placed objects (vector models in the two-dimensional case and polygonal models in the three- dimensional case) relevant. The aim of the study is to systematize methods that provide the formation of orthogonal polyhedra of various dimensions for describing objects and containers of arbitrary geometry. Methods for creating orthogonal polyhedra based on set-theoretic operations (addition, subtraction and intersection), analytical modeling using a set of functions and relational operators, as well as voxelization of fl and volumetric object models are considered. The use of set-theoretic operations is best suited for the manual creation of orthogonal polyhedra with relatively simple geometry. The method of analytical modeling is intended for the formation of voxelized objects based on geometric fi es described by a set of analytically specifi functions. The application of various relational operators to obtain orthogonal polyhedra that describe the contour, internal and external regions of analytical given objects is shown. An algorithm for creating a container in the form of an orthogonal polyhedron based on a given vector model is proposed, which makes it possible to solve problems of irregular packing of objects inside containers of arbitrary shape. All the methods presented in the article are programmatically implemented with a generalization in terms of dimension and are applicable to solving any types of cutting and packing problems.
{"title":"Methods of forming orthogonal polyhedra for cutting and packing objects of complex geometry","authors":"V. Chekanin, A. Chekanin","doi":"10.37791/2687-0649-2022-17-3-84-96","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-3-84-96","url":null,"abstract":"The article deals with the problem of packing objects of arbitrary geometry. Modern methods of designing irregular packing schemes use a mathematical model based on phi-functions and a hodograph vector function of dense placement. These methods make it possible to obtain exact solutions, but they are time-consuming and very sensitive to the dimension of the problem being solved and the degree of detail of the geometry of vector objects. The use of a discrete representation of placed objects in the form of orthogonal polyhedra can signifi increase the speed of construction a packing, which makes the problem of adequately transforming the shape of placed objects (vector models in the two-dimensional case and polygonal models in the three- dimensional case) relevant. The aim of the study is to systematize methods that provide the formation of orthogonal polyhedra of various dimensions for describing objects and containers of arbitrary geometry. Methods for creating orthogonal polyhedra based on set-theoretic operations (addition, subtraction and intersection), analytical modeling using a set of functions and relational operators, as well as voxelization of fl and volumetric object models are considered. The use of set-theoretic operations is best suited for the manual creation of orthogonal polyhedra with relatively simple geometry. The method of analytical modeling is intended for the formation of voxelized objects based on geometric fi es described by a set of analytically specifi functions. The application of various relational operators to obtain orthogonal polyhedra that describe the contour, internal and external regions of analytical given objects is shown. An algorithm for creating a container in the form of an orthogonal polyhedron based on a given vector model is proposed, which makes it possible to solve problems of irregular packing of objects inside containers of arbitrary shape. All the methods presented in the article are programmatically implemented with a generalization in terms of dimension and are applicable to solving any types of cutting and packing problems.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"48 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82717878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-31DOI: 10.37791/2687-0649-2022-17-2-133-142
A. Blinov, L. Konchina, M. Novikova, A. Borisov
The article considers the existing mathematical models of magneto-rheological substances and describes some of their properties. As a result of the open sources analysis, it was found that there are no exoskeleton models with variable-length links with adjustable stiffness, based on the application of magneto-rheological fluids. Therefore, the application of these fluids in other technical systems is considered. A mathematical model of an exoskeleton variable-length link with adjustable stiffness is proposed. This link can be used for supporting and strengthening the lower limbs of the human musculoskeletal system. The difference between the proposed mathematical model of the link and the existing ones lies in the fact that the section that changes its length is considered weighty. Therefore, the mathematical model of the link with a variable inertial characteristic, the moment of inertia relative to the axis perpendicular to the longitudinal axis of the link symmetry and passing through its beginning – the point where the link is fixed to the stationary mount with a cylindrical hinge, is considered. A method of motion control based on the assignment of differentiable functions is applied. The trajectory of the link movement is found, linear and angular velocities and accelerations are calculated. To showcase the link motion, the computer-animated visualization of the link motion control problem solution is presented. The control actions required for the implementation of the given motion have been calculated in the numerical experiment. The drag coefficient range of the magneto-rheological substance has been identified during the implementation of the proposed link motion. The software implementation of the proposed mathematical model of the exoskeleton variable-length link with adjustable stiffness has been done in the Wolfram Mathematica 11.3 universal computer math environment. The software package including the unit for deriving the differential equations of motion in analytical form, the kinematic trajectory synthesis unit, the computational experiment unit, and the unit for animated visualization of the model motion and its export in the wide-spread 'gif' video format has been developed.
{"title":"Applying the models of magneto-rheological substances in the study of exoskeleton variable-length link with adjustable stiffness","authors":"A. Blinov, L. Konchina, M. Novikova, A. Borisov","doi":"10.37791/2687-0649-2022-17-2-133-142","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-2-133-142","url":null,"abstract":"The article considers the existing mathematical models of magneto-rheological substances and describes some of their properties. As a result of the open sources analysis, it was found that there are no exoskeleton models with variable-length links with adjustable stiffness, based on the application of magneto-rheological fluids. Therefore, the application of these fluids in other technical systems is considered. A mathematical model of an exoskeleton variable-length link with adjustable stiffness is proposed. This link can be used for supporting and strengthening the lower limbs of the human musculoskeletal system. The difference between the proposed mathematical model of the link and the existing ones lies in the fact that the section that changes its length is considered weighty. Therefore, the mathematical model of the link with a variable inertial characteristic, the moment of inertia relative to the axis perpendicular to the longitudinal axis of the link symmetry and passing through its beginning – the point where the link is fixed to the stationary mount with a cylindrical hinge, is considered. A method of motion control based on the assignment of differentiable functions is applied. The trajectory of the link movement is found, linear and angular velocities and accelerations are calculated. To showcase the link motion, the computer-animated visualization of the link motion control problem solution is presented. The control actions required for the implementation of the given motion have been calculated in the numerical experiment. The drag coefficient range of the magneto-rheological substance has been identified during the implementation of the proposed link motion. The software implementation of the proposed mathematical model of the exoskeleton variable-length link with adjustable stiffness has been done in the Wolfram Mathematica 11.3 universal computer math environment. The software package including the unit for deriving the differential equations of motion in analytical form, the kinematic trajectory synthesis unit, the computational experiment unit, and the unit for animated visualization of the model motion and its export in the wide-spread 'gif' video format has been developed.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"6 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87306937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-31DOI: 10.37791/2687-0649-2022-17-2-20-30
M. Belyakov, M. G. Kulikova, Olga D. Anodina, Ekaterina I. Rysina
Optical spectral methods in the ultraviolet and visible regions can be used to develop transformer oil control technologies based on deep learning neural network models. The aim of the research is to identify informative spectral ranges of luminescent diagnostics for the automation system for monitoring the characteristics and parameters of transformer oil using deep learning neural networks. Measurements of the spectral characteristics of pure and spent transformer oil in the range of 180-700 nm were carried out on a diffraction spectrofluorimeter "Fluorat-02-Panorama". A qualitative and quantitative difference in the excitation spectra has been established: for waste oil, the spectra are shifted to the right and reduced by about four times to the maximum. The excitation maxima are located at wavelengths of 300, 322, 370 nm for pure and 388, 416 and 486 nm for waste oil. The photoluminescence spectra of pure oil at 300 nm excitation are a superposition of at least three curves, the largest of which has a maximum at 382 nm. For excitation of 370 nm, the spectrum is significantly wider and has maxima at wavelengths of 387, 405, 433-439 and 475-479 nm. The photoluminescence spectra of used oil are several times lower and have maxima at 446, 483 and 520-540 nm. The established excitation and luminescence ranges will be used when creating a methodology and installing quality control parameters of transformer oil during its operation. A deep learning neural network model based on the use of a self-organizing Kohonen map was also developed, which made it possible to predict the spectral characteristics of excitation based on the photoluminescence flow of transformer oil and, as a result, to determine the efficiency of the described method in industry through a decision-making system.
{"title":"Determination of informative spectral ranges for the development of a transformer oil control system using deep learning neural networks","authors":"M. Belyakov, M. G. Kulikova, Olga D. Anodina, Ekaterina I. Rysina","doi":"10.37791/2687-0649-2022-17-2-20-30","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-2-20-30","url":null,"abstract":"Optical spectral methods in the ultraviolet and visible regions can be used to develop transformer oil control technologies based on deep learning neural network models. The aim of the research is to identify informative spectral ranges of luminescent diagnostics for the automation system for monitoring the characteristics and parameters of transformer oil using deep learning neural networks. Measurements of the spectral characteristics of pure and spent transformer oil in the range of 180-700 nm were carried out on a diffraction spectrofluorimeter \"Fluorat-02-Panorama\". A qualitative and quantitative difference in the excitation spectra has been established: for waste oil, the spectra are shifted to the right and reduced by about four times to the maximum. The excitation maxima are located at wavelengths of 300, 322, 370 nm for pure and 388, 416 and 486 nm for waste oil. The photoluminescence spectra of pure oil at 300 nm excitation are a superposition of at least three curves, the largest of which has a maximum at 382 nm. For excitation of 370 nm, the spectrum is significantly wider and has maxima at wavelengths of 387, 405, 433-439 and 475-479 nm. The photoluminescence spectra of used oil are several times lower and have maxima at 446, 483 and 520-540 nm. The established excitation and luminescence ranges will be used when creating a methodology and installing quality control parameters of transformer oil during its operation. A deep learning neural network model based on the use of a self-organizing Kohonen map was also developed, which made it possible to predict the spectral characteristics of excitation based on the photoluminescence flow of transformer oil and, as a result, to determine the efficiency of the described method in industry through a decision-making system.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"23 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81811166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-31DOI: 10.37791/2687-0649-2022-17-2-5-19
I. Ilin, A. Levina, S. Kalyazina
Nowadays a production enterprise is inconceivable without the automation of all its processes – technological, production, and managerial. The efficiency of an enterprise largely depends on high-quality data processing within a single information space. The introduction of an integrated automated management system for an industrial enterprise, consistent with the business model, will eliminate many of the problems arising during creation, integration and development of automated systems, will create an effective enterprise management system and will reduce future costs of production modernization. Current trends of digital transformation increase the demand for an integrated business management system model, that would include a model of an integrated information management system as an integral part of it. The study aims to develop a reference functional model of mining enterprises, including a comprehensive vision of business, production and technological processes and their IT support. The model proposed is based on the analysis of existing international industry approaches to automation, as well as the experience and best practices of automation of mining enterprises. The methodological foundations of the research include enterprise architecture approach (including the concept of service-oriented architecture) and authors' function-oriented approach for engineering the IT architecture. The article describes a reference functional model of a mining enterprise, on the basis of which the structure of the mining enterprise IT-architecture functional structure is determined. The function-oriented approach for engineering IT-architecture as a reflection of the business functional structure is a good example of the symmetry phenomena in enterprise management. Further research will be devoted to the issues of designing an information exchange model and a data architecture model for the mining value chain and its individual parts in interconnection, as well as reflecting end-to-end processes of mining enterprises in the IT architecture based on the developed model for determining the boundaries of functional blocks of information systems
{"title":"Function-oriented approach to mining enterprise automation","authors":"I. Ilin, A. Levina, S. Kalyazina","doi":"10.37791/2687-0649-2022-17-2-5-19","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-2-5-19","url":null,"abstract":"Nowadays a production enterprise is inconceivable without the automation of all its processes – technological, production, and managerial. The efficiency of an enterprise largely depends on high-quality data processing within a single information space. The introduction of an integrated automated management system for an industrial enterprise, consistent with the business model, will eliminate many of the problems arising during creation, integration and development of automated systems, will create an effective enterprise management system and will reduce future costs of production modernization. Current trends of digital transformation increase the demand for an integrated business management system model, that would include a model of an integrated information management system as an integral part of it. The study aims to develop a reference functional model of mining enterprises, including a comprehensive vision of business, production and technological processes and their IT support. The model proposed is based on the analysis of existing international industry approaches to automation, as well as the experience and best practices of automation of mining enterprises. The methodological foundations of the research include enterprise architecture approach (including the concept of service-oriented architecture) and authors' function-oriented approach for engineering the IT architecture. The article describes a reference functional model of a mining enterprise, on the basis of which the structure of the mining enterprise IT-architecture functional structure is determined. The function-oriented approach for engineering IT-architecture as a reflection of the business functional structure is a good example of the symmetry phenomena in enterprise management. Further research will be devoted to the issues of designing an information exchange model and a data architecture model for the mining value chain and its individual parts in interconnection, as well as reflecting end-to-end processes of mining enterprises in the IT architecture based on the developed model for determining the boundaries of functional blocks of information systems","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"8 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81921010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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