Анализ данных науки, образования и инновационной деятельности с использованием методов анализа паттернов
World Bank data shows that education accounts for, on average, 13% of government expenditure in the world, effective spending being a priority. Position in international academic rankings has been a universally accepted, yet criticized, criterion of institutional effectiveness. No consistent positive correlation was revealed during research on how the size of government subsidies affected university ranking. Assessment methodology is adjusted to study the influence of public funding mechanisms on university ranking. Three mechanisms are investigated: formula based funding, performance based funding, and negotiated funding. The sample includes 107 European universities from 27 countries. For each of them, information on the funding model (or a combination of models), total annual revenue, proportion of public subsidies, ranking and ranking movements over the last decade is collected. Analysis results are used to group universities into two major categories: low-ranking universities (ranked in the top 200–500), which are mostly funded using formal mechanisms (formula- and performance based funding), and high-rankings universities (the top 100), which largely use the negotiated funding model (either alone or combined with formal models). This confirms previous research findings that the size of government subsidies has no impact on university ranking. A qualitative analysis of higher education funding patterns in Russia is performed. Formalization of all sources of university funding has become a major trend, yet this empirical study demonstrates that prioritization of formal criteria may be ineffective if Russian universities want to reach their ambitious goals of making it to the top 100 in international rankings.
We present a complex analysis of business models for large, medium and small Russian commercial banks from 2006 to 2009. The Russian banks are grouped based on homogeneity criteria of their financial and operational outcomes. The banks’ structure of assets and liabilities, profitability and liquidity ratio are taken into account. The results show how the banks are adjusted their business models before and after the financial turmoil taken place in 2008. In addition, the prevailing banking business models observed for the leading banks in Russia are defined. The banks often changing their business models are found and analyzed.
In article possible approaches to clustering of large city schools of the Russian Federation by results of their educational activity are studied. The extent to which a school has entered a particular cluster is determined by a number of objective conditions in which schools operate. Significant indicators of conditions affecting the EGE-results in schools were identified. It is shown that the studied indexes of the working conditions of schools are not sufficient for the correct clustering of schools according to the aggregated EGE-indicators.
In this article, authors analyze patterns of parental involvement in children’s schooling basing on the data of Monitoring of education markets and organizations completed in 2016. Authors argue that the involvement in children’s schooling is highly differentiated and suggest five types of it: regents, facilitators, sponsors, inspectors and invisibles. These types of parental involvement represented unequally depending on the socio-economic background of the family and children’s progress at school, plans for educational attainment and engagement in extracurricular activities.
The Age of Digital Economy can be described as encompassing and revolutionizing phenomenon fueled by the convergence of advancements in human communication, computing (computers, software, services) and content (publishing, entertainment and information providers), to create the interactive multimedia and the information highway . This new age is gradually forcing us to rethink the way we perceive the traditional definitions of economy, wealth creation, business organizations and other institutional structures.
The paper focuses on the main areas of knowledge management under the new economy conditions. The empirical study of several Russian companies shows the need for strong progressive leadership who is responsible for the transformation in the company.
The paper studies the communication and networking of employees and managers to combine their knowledge and creativity in the KM framework.
The work continues the research of constructing methods for analyzing patterns in parallel coordinates independent of the sequence of input data of the results. The basic operations on objects of ordinal-invariant pattern clusters are described. The assertion that the centroid of an ordinal-invariant pattern cluster belongs to the original cluster is proved, which allows one to estimate the intracluster object - centroid distances in the multidimensional feature space. Examples of revealing the structural similarity of objects in parallel coordinates are given. The main differences between the methods of analysis of patterns and cluster analysis are noted. The methodology of the centroid detection of the ordinal-invariant pattern- cluster is described. An algorithm for combining groups of objects based on their structural similarity, on the one hand, and minimizing intracluster distances, on the other, is proposed, which makes it possible to improve the accuracy of the final results and partially solve the problem of finding similar objects in the presence of error in the original data. The proposed algorithm uses the concept of intracluster distances “object - centroid” and satisfies the following conditions: endogenous determination of the number and composition of the desired groups of objects under study; low (relatively) computational complexity; independence of the original partition from the initial sequence of input data. The work of the proposed algorithm on classical data sets is demonstrated. The results of testing are presented and the clustering accuracy is increased.
Data Correcting Algorithms in Combinatorial Optimization focuses on algorithmic applications of the well known polynomially solvable special cases of computationally intractable problems. The purpose of this text is to design practically efficient algorithms for solving wide classes of combinatorial optimization problems. Researches, students and engineers will benefit from new bounds and branching rules in development efficient branch-and-bound type computational algorithms. This book examines applications for solving the Traveling Salesman Problem and its variations, Maximum Weight Independent Set Problem, Different Classes of Allocation and Cluster Analysis as well as some classes of Scheduling Problems. Data Correcting Algorithms in Combinatorial Optimization introduces the data correcting approach to algorithms which provide an answer to the following questions: how to construct a bound to the original intractable problem and find which element of the corrected instance one should branch such that the total size of search tree will be minimized. The PC time needed for solving intractable problems will be adjusted with the requirements for solving real world problems.
This paper presents a pattern behavioral analysis of 100 largest Russian commercial banks by total assets during an eight- year period: from the first quarter of 1999 to the second quarter of 2007. Bank performance indicators are analyzed. Structural similarities in the development of the banks are examined. A cluster analysis is applied to determine banks with a similar structure of operations. This analysis allows to estimate how the structure of the Russian banking system has been changing over time. In particular, it allows to identify prevailing patterns in the behavior of Russian commercial banks and to analyze the stability of their position in a particular pattern.