In this paper the authors describe the methodology for the statistical analysis of texts in social networks based on comparison of automatically generated frequency dictionaries by methods of correlation analysis. Psycholinguistic characteristics and coefficients of pairwise rank correlation are considered for comparing the frequency characteristics of texts in natural language

The work is devoted to the numerical simulation of plasma dynamics in the diamagnetic regime in an open magnetic trap. The hybrid model we use is based on the kinetic description of the ion and magnetohydrodynamic description of the electron plasma component. The disadvantage of the model is the conditional stability and the corresponding requirements for the time step. In practice, the double mesh nodes increase requires reducing the time step by factor of 6. For the typical times of the plasma processes of the order of 102 reciprocal ion cyclotron frequencies, the calculations on 100 × 500 grid require several days. At the same time, more than 85 % of the program operation time is occupied by the particle processing procedures, so their efficient implementation plays a key role in the decrease of the calculation times. In the proposed algorithm, we combine dynamic load balancing and vectorization of calculations for the electron density and current density computations. The results of numerical experiments are presented taking into account the substantially nonuniform distribution of the particles in the region and their increasing number due to the constant injection.

The article discusses modern methods and forms of information confrontation and information impact through information technology. The results of research on manipulating information by the search engine Google are presented. The significance and role of the USSR in the Second World War were considered as an information field. For this, factual material is used, a content analysis of articles by various researchers, search results of two different search engines is carried out. The materials of Russian and foreign representatives in relation to Google on cases of manipulation of algorithms for ranking the issued information have been investigated. A comparative analysis of the search results of two search engines in two languages is carried out. According to the conducted content analysis of sources and the criteria proposed by the author, the ranking of search results was carried out. Along with the positive goals pursued by modifications of search algorithms, additional tools have been identified that can be used as an informational influence and the actual results of manipulating information in the special elements of the Google search engine are presented. In continuation of the study, the importance of information resources occupying leading positions in the search results for the formation of users' worldview is indicated, and in this connection the resource wikipedia.org was analyzed. The author identifies the methods of manipulation used (silence and pressure positions) as the main ones in describing the role of the USSR in the Second World War. In the course of the study, materials are presented that indicate the possibility of using modern search information systems not only for obtaining commercial profit, but also within the framework of information warfare.

In the process of preparing a dissertation, the researcher is faced with the problems of determining the research topic, as well as the problems of writing a text for a particular specialty. To increase the objectivity of the classification of scientific texts by specialties, a system has been developed using machine learning algorithms. In the process of building the classification system, the following tasks were solved: development tools were identified, the collection and processing of initial data was carried out, machine learning models were built, and a web application was developed. The initial dataset is a sample of texts for the group of Russian scientific specialties “Informatics and Computer Engineering”. For the objectivity of the study, the initial data was filtered - the least representative classes were removed. Conversion of texts for vectorization was also carried out. For the vectorization of the source texts, the TF-IDF model was used, which allowed loading the entire data volume with limited technical capabilities. Multiclass logistic regression is chosen as a machine learning model used to classify a scientific specialty. For training, the initial data divided into 2 parts - training and test in a ratio of 80 to 20. Accuracy is used as a metric of the quality of the machine learning model. The choice of the metric is due to the sufficient balance of the classes. The model trained on the training data made it possible to achieve the accuracy of determining the scientific specialty on test data equal to 0.87. To use a ready-made machine learning model for classification of a scientific specialty, a web application has been developed using Flask. The web app is currently located at http://predict-spec.herokuapp.com/ The most urgent tasks for finalizing the system at the moment are: transferring a web application to a more powerful server, finalizing machine learning models, displaying visual information on the analyzed work.

This article discusses the main age-related features of the Internet use by adolescents and children. Today more and more computers are connected to the Internet. At the same time, connection via high-speed channels is becoming more common, both at work and at home. More and more children get the opportunity to work on the Internet. But at the same time, the problem of ensuring the safety of children on the Internet is becoming more acute. For this, a security monitor was developed, which has many functions that allow you to use the Internet more safely and under parental control. This security monitor is written in the web programming language JavaScript and PHP, which will allow using the system on almost all modern browsers and on any computer. The article also provides screenshots of the program's operation and a flowchart with a detailed description.

In this article, we investigate the issue of intelligibility of a foreign Slavic text for a Russian-speaking person which don’t know this language. The aim of this article is to find out what is the percentage of intelligible words in foreign text for such a person. As a main measuring tool, we used parallel cloze tests with omitted words in the Russian part. The task was to restore omitted words using the foreign part of a test (written in Ukrainian, Belorussian, Polish, Czech, Slovak, Serbian, Slovene, and Bulgarian languages) as a clue. As a baseline, we used a control group which solved a test without the foreign part. Our hypothesis was that the foreign text intelligibility could be defined as a difference between the mean percentage of correctly restored words for a group used a parallel text and the same percentage for a control group. The results of our experiments proved our hypothesis. All the pairs “omitted word - its translation” was divided into four groups: full and partial cognates, genetic cognates, non-cognates and false friends. The correlation between the mean intelligibility of a text in a given foreign language and the percentage of full and partial cognates was as high as 0.7; the same correlation for the other word groups was negative but not so deep. Therefore, we can state that the foreign text intelligibility is defined by the percentage of full and partial cognates but that is not the only parameter. The gathered data, containing the used tests, users’ answers and their background, and the software for its analysis is placed at https://github.com/klyshinsky/mutual_intelligibility_Russian.

The purpose of the article is to draw attention to the educational value of standards for professional qualifications in the field of IT in terms of training in complex professions and the formation of a professional community. A proposal has been formulated to improve the standard for the profession “system programmer”.

Coal mines are hazardous production facilities. Explosions of methane and coal dust are especially dangerous. Such accidents require prompt and accurate prediction of shock wave propagation parameters in mine workings, as well as knowledge of distances from the explosion epicenter to the boundaries of the dangerous zone. This is required to ensure the safety of people during mining rescue operations. The work presents the results of research to optimize the numerical calculations of the air shock wave through the turns and places of change in the geometry of mine workings by the method of Godunov first order of accuracy. An approach to optimization based on replacement of nodal spatial difference cells with one-dimensional ones is proposed. The criteria under which such substitution is possible are defined. Theoretical estimates of acceleration of numerical calculations are presented.