Development of Engineering Students Competencies Based on Cognitive Technologies in Conditions of Industry 4.0
Industry 4.0 and Society 5.0 concepts are actively developing all over the world. The accelerating transition to Industry 4.0 and Society 5.0 sets new requirements for the university education system in qualifications and competencies of engineering universities graduates. The article reveals the possibilities of using cognitive models in the professional training of research engineers for new industries. Authors used the modeling method for creating a cognitive and metacognitive model of the process. It can be used for the development of forming the optimal structure of higher professional engineering education. The article substantiates that the main tasks of modernization of pedagogical approaches in modern education, is to establish the compliance of educational products with the labor market requirements and transform the structure of vocational education, providing training for professional specialists required by specific employers. Conclusions are drawn about the important role of soft skills for engineering education in Industry 4.0. The results obtained in the study can be used for the engineering category of students.
With an increasing number of companies applying smart manufacturing (Industry 4.0) technologies, and therefore gathering records from multiple enterprise data sources, a potential for big data analytics (BDA) is seemingly limitless. Still not every firm that implemented smart manufacturing reports gathering or making use of big data emerging from those processes, let alone extracting value from them. This study investigates business value creation mechanisms from BDA in smart manufacturing. Relying on several use cases and project stories described in publicly available sources, we analyze key drivers, applications, barriers, success factors, and business benefits of BDA in smart manufacturing. We summarize our findings in a comprehensive framework capturing first- and second- order effects of BDA implementation on Industry 4.0 processes. Our work aims at contributing to the body of knowledge on BDA and smart manufacturing, and at guiding practitioners in identifying and assessing various application scenarios for those technologies.
Psychological markers associated with successful scientific work of biology students The paper report results from a psychological study of 90 biology students (Moscow State University) and five doctors of biology. Faculty expert opinions were used to determine ten most successful performers and ten poor performers among students. They were compared by several cognitive and personal factors. The paper shows that success in scientific work is connected not with separate cognitive, communicative and personal characteristics, but with their system interaction. When this interaction is not stable and optimal, efficiency of scientific work is low even if the level of personal development and cognitive abilities are relatively high. Keywords: science education, abilities for scientific work, cognitive abilities, personal characteristics, system of individual characteristics
The paper is focused on changes in higher engineering education in Russia over the last decade. We assume that, as a result of technological and organizational changes in the markets young engineers are taught to work in, changes in education may be called for. The key change in the markets for engineers in Russia consists of the transition from planned to market economy, and thus the appearance of markets per se, and also in a shift away from a focus on the defense industry. To identify the possible changes and assess the current state of engineering education, we compare opinions of four target groups: university administrators, students, recent graduates, and employers.
Materials of scientific and practical conference are included in the collection of works «Digital economy and «the Industry 4.0»: problems and prospects», prepared by laboratory «Innovative industrial economy» of Peter the Great St. Petersburg polytechnical university together with a number of the scientific organizations, higher education institutions, the industry entities.
In the collection of scientific works materials according to the theory of development of digital economy in modern conditions of the global competition, practical realization of the concept «the Industry 4.0», to research of problems and prospects of development of innovative activity of economic systems and enterprise entities, use of tools and valuation methods of an industrial development of regions, industries, the entities are reflected.
In the collection works of scientists and specialists of a number of higher education institutions, Russian Academies of Sciences institutes, the organizations, organizations and the entities, representatives of bodies of the public, municipal administration and executive power of Russia and foreign countries are provided.
Materials of the collection will be useful to teachers, scientists, specialists of the industrial, scientific enterprises, the organizations and organizations, and also graduate students, undergraduates and students.
This book presents the latest research perspectives on how the Industry 4.0 paradigm is challenging the process of technological and structural change and how the diversification of the economy affects structural transformation. It also explores the impact of fast-growing technologies on the transformation of socioeconomic and environmental systems, and asks whether structural and technological change can generate sustainable economic growth and employment. Further, the book presents the basic innovations (new technologies, materials, energy, etc) and industrial policies that can lead to such a structural change.
The paper explores a suitability of higher education quality measurement from student's point of view, and analyses results of interviewing of students from engineering specialties in Perm universities. Nonlinear Principal Components Analysis (NLPCA) in interpretation of Gifi system was used as the tool for data processing. It takes into account a dissimilar statistical nature of questionnaire indicators. The method can be very promising for various socio-economic researches.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.
The paper studies a problem of optimal insurer’s choice of a risk-sharing policy in a dynamic risk model, so-called Cramer-Lundberg process, over infinite time interval. Additional constraints are imposed on residual risks of insureds: on mean value or with probability one. An optimal control problem of minimizing a functional of the form of variation coefficient is solved. We show that: in the first case the optimum is achieved at stop loss insurance policies, in the second case the optimal insurance is a combination of stop loss and deductible policies. It is proved that the obtained results can be easily applied to problems with other optimization criteria: maximization of long-run utility and minimization of probability of a deviation from mean trajectory.