Modeling of the future in the programs of political parties

The paper addresses the problem of modeling and planning of the future. It presents the problems of developing a model of the future due to the ideologies and strategies of some ruling political parties. The authors deal with the means of expression of the model of the future as one of the most important elements of the lingvo-mental image of political world in the context of program documents of the parties. The authors examine a program of a party as a part of political communication system and characterize the model of the future. On the basis of comparative study the authors determine common and specific features of the model of the future expression. A comparative study of the model of the future expression on the material of ruling parties of Russia and a variety of foreign countries (the United States, Great Britain, France, and Italy) is extremely relevant in the current period of global economic crisis. Such a research provides the basis for the optimal model of the future determination that can become a universal one for the electorate of different countries. Thus, the authors reveal the most advanced model of the future representation

Digital Platform for Modeling the Development of Regional Innovation Systems of Russian Federation

The paper aims at the design of a digital tool for analyzing the impact of scientific and technological progress on socioeconomic problems and sustainable development of the region. The research focuses on the consistent development of a digital platform for analyzing and visualizing digital data on regional innovation development, as well as predicting the sustainable development of regions based on the available regional infrastructure of innovation systems and the Russian regions' cluster structure. When designing the digital platform, we gave special attention to ensuring efficient data collection, processing, and analysis processes required for studying the socio-economic system. In the course of the work, an automated process of working with data was developed. The digital platform is being developed as a flexible tool for a wide range of users, from research centers, investors, and private enterprises to individual users interested in regional innovation development models. As part of the work, the process of selecting technical tools for the software implementation of the platform in terms of tasks and technical features of designing digital platforms is presented. The result of the work is a prototype of the Russian regional innovation system digital platform with the implemented functionality of a personal account, a module of simulation experiments, and various approaches to data analysis and visualization. The research is carried out as part of a project to develop a digital model of the regional innovation system of the Russian Federation as a driver of sustainable development

Intelligent Data Analysis for Infection Spread Prediction

Intelligent data analysis based on artificial intelligence and Big Data tools is widely used by the scientific community to overcome global challenges. One of these challenges is the worldwide coronavirus pandemic, which began in early 2020. Data science not only provides an opportunity to assess the impact caused by a pandemic, but also to predict the infection spread. In addition, the model expansion by economic, social, and infrastructural factors makes it possible to predict changes in all spheres of human activity in competitive epidemiological conditions. This article is devoted to the use of anonymized and personal data in predicting the coronavirus infection spread. The basic “Susceptible–Exposed–Infected–Recovered” model was extended by including a set of demographic, administrative, and social factors. The developed model is more predictive and applicable in assessing future pandemic impact. After a series of simulation experiment results, we concluded that personal data use in high-level modeling of the infection spread is excessive

Intelligent Data Analysis for Infection Spread Prediction

Intelligent data analysis based on artificial intelligence and Big Data tools is widely used by the scientific community to overcome global challenges. One of these challenges is the worldwide coronavirus pandemic, which began in early 2020. Data science not only provides an opportunity to assess the impact caused by a pandemic, but also to predict the infection spread. In addition, the model expansion by economic, social, and infrastructural factors makes it possible to predict changes in all spheres of human activity in competitive epidemiological conditions. This article is devoted to the use of anonymized and personal data in predicting the coronavirus infection spread. The basic “Susceptible–Exposed–Infected–Recovered” model was extended by including a set of demographic, administrative, and social factors. The developed model is more predictive and applicable in assessing future pandemic impact. After a series of simulation experiment results, we concluded that personal data use in high-level modeling of the infection spread is excessive

Hardware-software geo-information system for positioning objects

The project is dedicated to the development of experimental samples of hardware-software complexes for seamless positioning of objects inside and outside the buildings to ensure the implementation of the principle “always and everywhere”. The work substantiates the need for developing a project dedicated to the creation of a hardware-software geo-information system for positioning objects. To achieve this goal, the analysis of shortcomings of existing technologies for object positioning is carried out. This analysis allowed identifying the main tasks that need to be addressed. A review of existing approaches to the development of geographic information positioning systems was held. The advantages of the developed geoinformation complex for object positioning are described. The main results and the effect of the project are characterized

Modeling of the future in the programs of political parties

The paper addresses the problem of modeling and planning of the future. It presents the problems of developing a model of the future due to the ideologies and strategies of some ruling political parties. The authors deal with the means of expression of the model of the future as one of the most important elements of the lingvo-mental image of political world in the context of program documents of the parties. The authors examine a program of a party as a part of political communication system and characterize the model of the future. On the basis of comparative study the authors determine common and specific features of the model of the future expression. A comparative study of the model of the future expression on the material of ruling parties of Russia and a variety of foreign countries (the United States, Great Britain, France, and Italy) is extremely relevant in the current period of global economic crisis. Such a research provides the basis for the optimal model of the future determination that can become a universal one for the electorate of different countries. Thus, the authors reveal the most advanced model of the future representation

Complex Method of the Consumer Value Estimation on the Way to Risk-Free and Sustainable Production

Sustainable consumption and production strive for the rational management of natural resources, which implies a transition to the production of fewer goods with the greatest consumer value. Consequently, the consumer value assessment is a key task in the product and service design. However, a large number of applied practices for assessing consumer value is a challenge for researchers. Multiple heterogeneous solutions without a common classification and structure do not allow comparing methods with each other. Thus, there is a demand for some universal algorithm for assessing consumer value, which would be a model for the development of individual industry practices. Therefore, the present research aims to develop a universal algorithm for assessing consumer value, which is a unified sample. The work analyzes the current expertise in assessing consumer value. The paper provides a comparison of mathematical tools for aggregate indicators in order to develop a general formula for assessing consumer value. As a result, an algorithm for assessing consumer value has been developed, which includes the following stages: market segmentation by consumer groups, taking into account their personal characteristics and needs; product hierarchical division into groups according to indicators valuable to the consumer; selection of a scale for evaluating indicators; hierarchical convolution, calculation of the consumer value of selected indicators and their aggregation into a final assessment in accordance with coefficients obtained as a result of the initial data analysis. As part of the algorithm verification, an example of the implementation of the algorithm steps based on expert assessment of the tourist product characteristics is proposed. At the next stage of the study, a register of mathematical tools will be specified to ensure the implementation of the algorithm steps, and practical testing on real data on several products from different industries