Использование инструментального программного комплекса РДС (Расчет Динамических Систем) в обучении
Various aspects of realization of the right of the Jewish population of the Russian Empire on access to the higher education are considered by the authors. They trace interrelation of processes of expansion of access to the higher education and formations of institutions of Civil Society in Late Imperial Russia.
In the publication we describe Russian regional markets of higher education. We consider the following indicators of the markets: size in terms of students per 10 000 of population; its institutional structure – number of public and private institutions, universities and their local branches; program diversity; level and dynamics of tuition fees during recent years; and levels of market concentration in higher education. For each key indicator we present geographical maps that characterize differentiation of the regional markets. We also analyze indicators of regional markets of higher education in conjunction with clusters of Russian regions outlined by Independent Institute on Social Policy (2006) on the basis of socio-economic indicators and derive meaningful conclusions on differentiation of key indicators of higher education markets. We show that in Russia the level of regional development corresponds to the level of concentration and diversification at regional higher education markets.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability