Данное учебное пособие включает задания для практических работ по дисциплине «Цифровые технологии», который преподается для студентов, обучаемых по направлениям бизнес-информатики, социологии, менеджмента в РАНХиГС. Также пособие может быть полезно преподавателями, аспирантами, интересующимися вопросами визуализации данных, автоматизации рутинных функций при расчетах,и студентам различных IT-специальностей при самоподготовке.

The purpose of this research is the development of an information system that would allow to carry out quality management in terms of the results of the learning process. The work is of practical importance, as algorithm for assessing the learning process is proposed, which is implemented and integrated into the information system of monitoring, evaluation, correction of the learning process for any discipline. With the help of the developed module it is possible to evaluate the degree of mastering competences by students and to carry out long-term planning of the educational process. In the work, the process of teaching students is modeled on the basis of studies of general information processes in educational environments. A dynamic model is constructed in the notation of colored hierarchical Petri nets. The simulation model of one of the stages of mastering the discipline of the curriculum is analyzed. Methods of statistical analysis developed an algorithm for rating the work of the department. The equation of the discriminant function was obtained, which served as a rating for real departments of the Moscow City University.

The article is devoted to improving the quality of management of an educational organization by automating personalized data collection, storage and ranking in the preparation of specialists in the on-Board communication systems. The authors have developed a module of the university's corporate system - an electronic portfolio of students, which implements a multi-criteria optimization method for calculating students' ratings based on the collected and stored data. The object of the study is multicriteria ranking methods. The subject of the research is the automated calculation of the student rating in the electronic portfolio. The aim of the study is to develop tools for collecting, storing and processing data on individual student achievements and the implementation of a mathematical method of multicriteria optimization for ranking students based on portfolio data. The practical significance of the study is to provide a tool for effective management of the learning process. Method and toolkit. A prototype of the module of the corporate system of the university “Electronic Portfolio” based on the developed configuration in “1C: Enterprise 8.3” is presented. For the ranking of students in the module for data analysis, a special case of the method of ranking alternatives is implemented - pairwise comparison according to their relative importance, using a unified scale of relations. Results. The authors described the scheme of functioning of is “Electronic portfolio”, showed the scheme of interaction of processes on formation of portfolio, presented the scheme of business processes at calculation of an individual rating. A fragment of the sample on which the performance of the multi-criteria optimization block was checked is shown. The criteria taking part in calculations and the rule of selection of alternatives for finding the optimal solution are de-scribed. Discussion and Conclusion. The paper presents the results of the IP block on ranking the list of students. The results of the calculations coincide with the practical results.

Introduction. The paper considers improving the management quality of an educational organization through automating the personalized data collection, storage and ranking. The authors have developed a module of the university corporate system, an ePortfolio of students, which implements a multicriteria optimization method for calculating the students’ rating on the basis of the collected and stored data. The study object is multicriteria ranking methods. The subject of the study is the automated calculation of student’s rating within the electronic portfolio. The study objective is to develop tools for collecting, storing and processing data on individual achievements of students and the implementation of the mathematical method of multicriteria optimization for ranking students on the basis of the portfolio data. Practical implications include development of a tool for an effective management of the educational process.Materials and Methods. A prototype module of the university corporate system “ePortfolio” on the platform of 1C: Enterprise 8.3 is presented. To rank students, a special case of the alternative ranking method is implemented in the block of the data analysis module – pairwise comparison in order of their relative importance. At that, a unified scale of relations was used.Research Results. The authors described the scheme of the information system (IS) operation “ePortfolio”, presented a process interaction pattern for the portfolio formation, as well as a diagram of business processes under calculating an individual rating. A fragment of the sample is shown on which the performance of the multicriteria optimization block has been tested. The criteria of the calculations are described, as well as the rule of screening alternatives for solving for the optimum.Discussion and Conclusion. The paper presents the results of the IS block operation on ranking a list of students. The calculation results coincide with the practical data.

A new approach to analysis of the molecule-descriptor matrix in the structure-property problem, based on the fuzzy cluster structure of the training sample, is developed. Methods for constructing fast prediction rejection rules and for the search of outliers in a training sample are described. To that end, a special space of easily computed descriptors is introduced. Optimization of the classifying function with respect to the parameters of fuzzy classification is considered. Prognostic models with a high quality of prediction, based on this approach, are proposed. Comparison of models is performed, which shows the efficiency of the described methods.

A new approach for analyzing the "molecule-descriptor" matrix for the QSAR problem (Quantitative Structure-Activity Relationship) based on a fuzzy cluster structure of the learning sample is presented. The ways for generating fast rules for refusing prediction and searching the spikes in the learning sample are described. For this purpose, a special space of descriptors, simple for calculation, is introduced. The ways for optimizing the discriminant function according to fuzzy clustering parameters are examined. Highly predictive models based on the presented approach have been generated. The models are compared, and the efficiency of the described methods is revealed.

A new approach for analyzing the moleculedescriptor matrix for the QSAR problem (Quantitative StructureActivity Relationship) based on a fuzzy cluster structure of the learning sample is presented. The ways for generating fast rules for refusing prediction and searching the spikes in the learning sample are described. For this purpose, a special space of descriptors, simple for calculation, is introduced. The ways for optimizing the discriminant function according to fuzzy clustering parameters are examined. Highly predictive models based on the presented approach have been generated. The models are compared, and the efficiency of the described methods is revealed.

The structure-property correlation equations for the activation energies of thermal decomposition of nitro compounds in the gaseous phase were obtained based on structural descriptors. The equations were constructed using the BIBIGON computing program system for the data base, which consists of 90 nitro compounds belonging to various chemical classes; the correlation coefficient R is 0.986.

A graph theory approach for constructing structural descriptors for finding quantitative structure-property relationships (QSPR) has been suggested. A complete enumeration of the linear fragments (chains of atoms) of molecular structures has been performed. Atoms in chains differ both by the type of element and by the marker that reflects their chemical and topological peculiarities. QSPR-models have been developed for various classes of chemical compounds for estimation of lipophilicity, enthalpy of formation, boiling points, and chromatographic retention time. All of these QSPR-models have been simulated by a BIBIGON MATCH PC-computer system (Basic Instrument for Building/Interactive Generation of Optimized Networks of Marked-Atom Chains), which implements the method suggested.

In spite of the great ecological importance of euphausiids in large areas of the sea, very little is known about their early developmental stages. During the 40th and 41st cruises of RV “Vityaz” (USSR) in the western part of the Indian Ocean, new information was obtained on the development of 2 species common in that area: Euphausia diomedeae and Slylocheiron carinatum. In E. diomedeae, the time between fertilization and hatching of the nauplius amounts to about 16 h; the metanauplius stage lasts 2 days, the calyptopis stage I also 2 days, and the calyptopis stage III up to 4 days, at water temperatures ranging from 22° to 26°C. The developmental stages of both species are described and illustrated.