A. Shevchenko, A. Shevchenko, O. Tyatyushkina, S. Ulyanov
{"title":"Intelligent robust controller based on cognitive computing technologies. Pt. 1: cognitive Control models with THE BRAIN emotional learning","authors":"A. Shevchenko, A. Shevchenko, O. Tyatyushkina, S. Ulyanov","doi":"10.37005/2071-9612-2020-4-90-134","DOIUrl":"https://doi.org/10.37005/2071-9612-2020-4-90-134","url":null,"abstract":"n on-linecontrol and decision-making systems, emotional brain training is a preferred methodology (compared to stochastic gradient-based and evolutionary algorithms) due to its low computational complexity and fast robust learning. To describe the emotional learning of the brain, a mathematical model was created —the brain emotional learning controller (BELC). The design of intelligent systems based on emotional signals basedoncontrol methods assoft computing technologies: artificial neural networks, fuzzy control and genetic algorithms. Based on the simulated mathematical model of mammals BEL, a controller architecture has been developed. Applied approachcalled “Brain Emotional Learning Based Intelligent Controller” (BELBIC) —a neurobiologically motivated intelligent controller based on a computational model of emotional learning in the mammalian limbic system. The article describes applied models of intelligent regulators based on emotional learning of the brain. BELBIC's learning capabilities;versatility and low computational complexity make it a very promising toolkitfor on-lineapplications.","PeriodicalId":299093,"journal":{"name":"System Analysis in Science and Education","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123508348","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}
{"title":"Problems of model development of modern robotics and the difficulties of forming an innovative educational process","authors":"O. Tyatyushkina","doi":"10.37005/2071-9612-2020-4-71-78","DOIUrl":"https://doi.org/10.37005/2071-9612-2020-4-71-78","url":null,"abstract":"The objectively necessary and possible socio-technical and socio-economic conditions for the development of a scientific-methodological, software-algorithmic and technical basis in the development of intelligent robotic technology are considered. The fundamentals of the development methodology and examples of information technologies of the educational process in intelligent robotics are briefly discussed.","PeriodicalId":299093,"journal":{"name":"System Analysis in Science and Education","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133207250","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}
M. Bashashin, A. Yermekova, E. Zemlyanaya, M. Kakenov, K. Lukyanov
{"title":"Аnalysis of differential cross sections of 12,14ВЕ+2С with energy of 56 mev / nucleon on the basis of parallel implementation of a four–parameter microscopic nucleus–nucleus scattering model","authors":"M. Bashashin, A. Yermekova, E. Zemlyanaya, M. Kakenov, K. Lukyanov","doi":"10.37005/2071-9612-2020-4-10-19","DOIUrl":"https://doi.org/10.37005/2071-9612-2020-4-10-19","url":null,"abstract":"The MPI/C++ /Fortran package of computer codes has been developed for high-performance numerical analysis of experimental data on elastic nucleus-nucleus scattering within a microscopic model of optical potential. In the package, a modified DWUCK4 Fortran-code for calculating the physical characteristics of elastic scattering based on a numerical solution of the corresponding Schrödingerequation has been incorporated into the C++ framework, which is responsible for the input-output procedure and a comparison of numerical results with experimental data. MPI-based parallelism allows efficient calculations of the observables depending on a wide range of parameters of real and imaginary parts of the microscopic OP. The package has been used to analyze experimental data on differential cross sections of the 12,14Ве+12Сelastic scattering.","PeriodicalId":299093,"journal":{"name":"System Analysis in Science and Education","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114949758","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}
Sergey Belov, J. Javadzade, V. Korenkov, I. Kadochnikov, P. Zrelov
{"title":"Data approach for the studies of the job market and related areas","authors":"Sergey Belov, J. Javadzade, V. Korenkov, I. Kadochnikov, P. Zrelov","doi":"10.37005/2071-9612-2020-4-147-154","DOIUrl":"https://doi.org/10.37005/2071-9612-2020-4-147-154","url":null,"abstract":"This paper discusses some approaches to intellectual text analysis in application to automated monitoring of the labour market. The construction of an analytical system based on Big Data technologies for the labour market is describedd. Were compared the combinations of methods of extracting semantic information about objects and connections between them (for example, from job advertisements) from specialized texts. A system for monitoring the Russian labour market has been created, and the work is underway to include other countries in the analysis. The considered approaches and methods can be widely used toextract knowledge from large amounts of texts.","PeriodicalId":299093,"journal":{"name":"System Analysis in Science and Education","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114166919","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}
{"title":"New educational trends and challenges. Determination of the level of digital competence","authors":"O. Sheveleva, A. Bugrov","doi":"10.37005/2071-9612-2020-4-79-89","DOIUrl":"https://doi.org/10.37005/2071-9612-2020-4-79-89","url":null,"abstract":"The development of information technology leads to a change in old paradigms in all areas. The state and employers set new requirements for specialists, such as digital competencies (DC). The article presents the results of a study of the general interest and interest of the academic community in the DC. Additionally, we made a primary analysis of the existing methods of DC level detection, presented in the Russian-language academic (RLA) literature within 2015-2020 in the work. In preliminary the work conclusion was estimated that this issue has not been considered enough in RLA.","PeriodicalId":299093,"journal":{"name":"System Analysis in Science and Education","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131444821","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}
{"title":"Prototype of software and technological support quality management of knowledge acquisition by university students","authors":"A. D. Rybakina, V. Dobrinin","doi":"10.37005/2071-9612-2020-4-57-70","DOIUrl":"https://doi.org/10.37005/2071-9612-2020-4-57-70","url":null,"abstract":"Currently there are a large number of services and platform for organizing remote learning and manag-ing the quality of knowledge acquisition by university students. For example, Moodle, Ispring, Edmodo, Ёстади. All of them have a testing device, the ability to store and present theoretical material in different formats: in the form of audio, video, test, etc.Despite this, some areas are developing related to the improvement of tools and tools for knowledge control, analysis ofthe quality of the learning process, analysis of the quality of educational and methodological materials. There is a need for mobile components that allow students to evaluate and analyze the acquired knowledge in the learning process, actively identify missing knowledge, receive recommendations and advice at the right time, and thus effectively use classroom and extracurricular time.","PeriodicalId":299093,"journal":{"name":"System Analysis in Science and Education","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133904131","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}
{"title":"The prospects of a CMS development","authors":"D. Gutovskiy, V. Dobrinin","doi":"10.37005/2071-9612-2020-4-25-36","DOIUrl":"https://doi.org/10.37005/2071-9612-2020-4-25-36","url":null,"abstract":"This article contains the description of the prospects of a CMS development and the short description of the stages of the Internet-formation before an appearance of the CMS. And the assumed way of a CMS development along the MODx-scenario is described in this article.","PeriodicalId":299093,"journal":{"name":"System Analysis in Science and Education","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114165793","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}
{"title":"Research of the possibility of reducing corruption in Russia based on mathematical multi–factor models","authors":"I. Antipin, Y. Volodina","doi":"10.37005/2071-9612-2020-4-1-9","DOIUrl":"https://doi.org/10.37005/2071-9612-2020-4-1-9","url":null,"abstract":"This article emphasizes the modern trends in the formation of corruption in state and municipal management in Russia. The main features of the introduction of new anti-corruption tools are given. The main approaches to implementing management decisions are presented. In modern conditions, the need to transition the economy to the digital reality of the XXI century becomes urgent, which will certainly contribute to the eradication of corruption at various levels. For the effective socio-economic progress, anti-corruption is the most important strategic task. Based on the analysis, forecast indicators of corruptionwere obtained, on the basis of which recommendations were identified that minimize the degree of corruption in our country.","PeriodicalId":299093,"journal":{"name":"System Analysis in Science and Education","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122208304","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}
{"title":"Combined automated searching for coassociative relations as a preprocessing step in exploratory multispectral data analysis","authors":"D. Vakulenko, A. Kravets","doi":"10.37005/2071-9612-2020-4-20-24","DOIUrl":"https://doi.org/10.37005/2071-9612-2020-4-20-24","url":null,"abstract":"In current research a combination of several techniques–group of cluster analysis approaches and machine learning methods have been used to investigate the satellite multispectral imagery of cropland.The primary work with data makes emphasis on clustering by agroup of algorithms. The method proves to make the neural network detecting of pixels with similar signatures in much more accurate way and allows to interpret crop growth processescorrectly.The technique appears useful in order to form a representativetraining set for powerful neural image classification model to provide the accuracy of revealing structural dependencies and carrying them over on new data.The theoreticalpart of research is given to plan further experimental researchwork.","PeriodicalId":299093,"journal":{"name":"System Analysis in Science and Education","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128789477","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}
{"title":"Recognition recipes with deep machine learning","authors":"S. Ulyanov, A. Filipyev, Kirill Koshelev","doi":"10.1007/978-3-030-63322-6_51","DOIUrl":"https://doi.org/10.1007/978-3-030-63322-6_51","url":null,"abstract":"","PeriodicalId":299093,"journal":{"name":"System Analysis in Science and Education","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131676100","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}