Abstract:

To determine the most effective approach for solving the task of classifying the emotional tone of a message, we trained selected neural network models on various sets of training data. Next, based on the performance metric of the percentage of correctly classified responses on a test data set, we compared combinations of training data sets and various models trained on them. During the writing of this article, we trained four neural network models on three different sets of training data. By comparing the accuracy of the responses from each model trained on different training data sets, conclusions were drawn regarding the neural network model best suited for solving the task at hand.

Abstract: Actual problem of modern theory and methods of teaching mathematics – teaching methods of self-regulation in the process of solving mathematical tasks.

Abstract:

The problem of finding the most relevant documents as a result of an extended and refined query is considered. For this, a search model and a text preprocessing mechanism are proposed, as well as the joint use of a search engine and a neural network model built on the basis of an index using word2vec algorithms to generate an extended query with synonyms and refine search results based on a selection of similar documents in a digital semantic library. The paper investigates the construction of a vector representation of documents based on paragraphs in relation to the data array of the digital semantic library LibMeta. Each piece of text is labeled. Both the whole document and its separate parts can be marked. The problem of enriching user queries with synonyms was solved, then when building a search model together with word2vec algorithms, an approach of "indexing first, then training" was used to cover more information and give more accurate search results. The model was trained on the basis of the library's mathematical content. Examples of training, extended query and search quality assessment using training and synonyms are given.

Abstract: This article presents the results of a systematic literature review on the matter of universities’ experience with implementation of digital learning. The findings point out the advantages, disadvantages, discrepancies, problems, challenges, and possible solutions. The conclusion section contains general expectations in respect of the quality and effectiveness of digital education. Finally, the recommendations on how to minimize negative consequences are formulated.

Abstract: The paper is aimed to propose the machine learning model for determining the relationship between data of social network profile and academic success of students and predicting the success using the data.

Abstract: The following questions are mentioned: teaching mathematics at the present stage and its purpose; mathematical language students – as a major component of mathematical training; scientific – psychological and scientific – methodical speech of pupils of secondary schools; the development of mathematical speech of pupils.

Abstract:

In this paper one of the possible implementations of cooperative education models based on STAD (Student Teams-achievement Divisions) strategy of cooperative learning in LMS (Learning Management System) is described. The approaches of this learning methodology increase the level of teamwork skills, need in further professional activity, and their injection into LMS can help to automate and optimize some processes and open new opportunities for implementation of new instruments.  

Abstract:

This paper focuses on the use of a linguistics-based method for automatic object-oriented sentiment analyses. The study was conducted as part of SentiRuEval automatic sentiment analysis system testing cycle. The original task was to extract users’ opinions (positive, negative, neutral) about telecom companies, expressed in tweets and news. In this study news was excluded from the dataset because, being formal texts, news significantly differs from informal ones in its structure and vocabulary and therefore demands a different approach. Only linguistic approach based on syntactic and semantic analysis was used. In this approach, a sentiment-bearing word or expression is linked to its target object at either of two stages, which perform successively. The first stage includes usage of semantic templates matching the dependence tree, and the second stage involves heuristics for linking sentiment expressions and their target objects when syntactic relations between them do not exist. No machine learning was used. The method showed a very high quality, which roughly coincides with the best results of machine learning methods and hybrid approaches.

Abstract: Currently, there are a huge number of works dedicated to semantic role labeling of English texts [1–3]. However, semantic role labeling of Russian texts was an unexplored area for many years due to the lack of train and test corpora. Semantic role labeling of Russian Texts was widely disseminated after the appearance of the FrameBank corpus [4]. In this approach, we analyzed the influence of the word embedding models on the quality of semantic role labeling of Russian texts. Micro- and macro- F1 scores on word2vec [5], fastText [6], ELMo [7] embedding models were calculated. The set of experiments have shown that fastText models averaged slightly better than word2vec models as applied to Russian FrameBank corpus. The higher micro- and macro- F1 scores were obtained on deep tokenized word representation model ELMo in relation to classical shallow embedding models.

Abstract:

For support of adaptive training and educational analytics in the intellectual learning systems, it is necessary to collect, process data on progress of the student and his various individual characteristics. It can be realized by means of the student model. The analysis of approaches to modeling of the student has shown that application of several types of models is an optimal solution, considering requirements to the learning system. Three approaches were chosen and united into one model: overlay, Bayesian network, error model. Use of overlay model allows to build individual trajectories of student training. Bayesian networks realize competence-based approach in training. The model of mistakes keeps track of wrong knowledge of the student and helps the student to correct them at early stages. The student model uniting in itself these approaches is more suitable for realization of the personalized training, allows to keep track of progress of the student according to various characteristics and also gives the chance to easily submit the card of subjects, knowledge, competence of the student of various areas in the form of the count that is quite convenient and clear representation.

Abstract:

The work presents a digital platform for supercomputer modeling the problems of spraying the particles on substrates. The purpose of this work is to discuss the general architecture, technology stack and implementation features of the platform's user interface. The platform is based on web technologies for access and management of calculations, which allow implementing a user system for conducting a full cycle of a computational experiment, including the configuration of applied applications, their launch on remote computing resources, monitoring the completion of tasks, analysis and interactive visualization of results. User interaction with computing resources is implemented through the graphical interface that does not require the client computer to have any additional software, except actual version of a modern web browser. An important advantage of the platform is the ability to make large-scale computer research in a multi-user mode that is based on the natural principles of building client-server applications. The presented digital web platform was successfully tested on computing clusters of the KIAM RAS in solving a number of the topical mathematical problems of nanotechnology. Also, with its help, for the last 3 years, group training of MIPT students in modern information technologies has been carried out.

Abstract: The article raises questions of overcoming the crisis in the library through the merger of informational library resources with the RUDN’s Learning Management System. The new role of the library in the creation and support of the Learning Management System, and integration of the electronic library system and other databases with the Learning Management System is discussed.

Abstract: The issue of STEM education in a modern school and methodological approaches to its implementation on the subjects of the natural science cycle as part of project activities are considered. An example of the stages of work on a project, a breakdown into subject areas, is given. Since STEM education involves not only gaining knowledge in individual subjects, but also putting them into practice, the key point in working on a project is practical application. Within the framework of the subject area of mathematics and computer science, this involves making calculations and presenting the final results using modern technical means. Thus, the subject of mathematics moves from the framework of academic knowledge to the framework of practical skills. In particular, the article provides an example of the formation of a student’s financial literacy as part of a project. STEM-training allows you to combine scientific methods, mathematical modeling, technological applications and engineering design. Thus, innovative critical thinking is formed, the opportunity and need for integrated training on topics within the framework of which active communication of students occurs and a new educational space is formed.

Abstract: The use of different metaprogramming mechanisms for program libraries development in Java may have some negative effect on build time and end products. The article is aimed to describe metaprogramming mechanisms in the Java language and present the results of experiments that compare the impact of approaches on the build time of small and large projects.

Abstract:

Relevance of the issue under study is due to tenuity of methods proposed by other researchers that use simple heuristics or machine learning algorithms. The purpose of the article is to provide better way to extract titles from scientific PDF documents and offer better and more reasonable approach to title selection generally. The leading approach to the study is regard as many cases and problems appeared during extraction as possible and find an approach to solve all of them. The results showed the efficiency of chosen approach in case of having a document set with all of considered problems. The research highlights that deep analysis of current task problem is a perspective to make the best solutions and tools. The article may be useful for all researchers and developers who often encounter the problem of document structural analysis or title detection as secondary task of a main program workflow.

Abstract:

The article discusses various solutions that exist in the field of remote control of robotic devices equipped with manipulators. New approaches are presented for organizing joint telecontrol of multiple manipulators using various user inputs. The following usage scenarios are considered: the architecture of a system with many manipulators and user control interfaces, including such promising areas as deep machine learning and neural interfaces.

Abstract: The problem of the formation of personality activity in teaching mathematics is very complex. The question remains for the teacher of mathematics: what methods to apply so that teaching mathematics is effective and practice-oriented, develops personality activity in collective mathematical activity? The paper describes the specifics of the use of case technology in teaching mathematics.

Abstract:

This paper presents a neuro-fuzzy algorithm for high-speed grayscale image segmentation based on a modified defuzzification method using triangular membership functions. The aim of the study is to analyze the effect of simplifying the defuzzification formula on the accuracy and contrast of object selection. The proposed approach includes adaptive learning of the weight coefficient, which allows dynamically adjusting the defuzzification process depending on the target values. The paper compares the basic method of averaging membership values and a modified version taking into account nonlinear weights. Experiments conducted on 1024x720 images demonstrate that the developed algorithm provides high segmentation accuracy and improved object contrast with minimal computational costs. The results confirm the superiority of the proposed method over traditional approaches, emphasizing the prospects for applying artificial intelligence in computer vision problems.

Abstract: This review discusses methods and algorithms for increasing linked data expressiveness which are prepared for Web publication. The main approaches to the enrichment of ontologies are considered, the methods on which they are based and the tools for implementing the corresponding methods are described.The main stage in the general scheme of the related data life cycle in a cloud of Linked Open Data is the stage of building a set of related RDF- triples. To improve the classification of data and the analysis of their quality, various methods are used to increase the expressiveness of related data. The main ideas of these methods are concerned with the enrichment of existing ontologies (an expansion of the basic scheme of knowledge) by adding or improving terminological axioms. Enrichment methods are based on methods used in various fields, such as knowledge representation, machine learning, statistics, natural language processing, analysis of formal concepts, and game theory.

Abstract:

An overview of the methods for measuring progress of software development within flexible SCRUM methodology is given, as well as a description of a software tool development that monitors current status of project by time characteristics. The tool based on the characteristics can notificate project manager about events he have to pay attention in current project situation and help him to achieve effective results.

Abstract:

Today, users of mobile applications in different areas leave a huge amount of digital footprint. The main types of digital footprints are text, photos, videos, audio, and current location. To assist the teacher in horizontal learning, a mobile application that collects all of the above types of digital footprint was developed as well as web application that analyzes it.

Abstract: The paper is aimed to describe a system with some mechanisms for using mobile devices in distributed computing. Emphasis is placed on components of the system which control tasks and distribute resources.

Abstract:

The article is devoted to the development of solutions in the project of a simulator for teaching programming, intended for initial familiarization with the basic concepts of process interaction and calculation management. No matter how complex the world of parallelism is, the programmer training system will have to master it and create a methodology for fully familiarizing itself with its non-obvious phenomena. The simulator is based on the experience of controlling the interaction of toy robots moving on a checkered board. The article material is of interest to programmers, students and graduate students specializing in the field of system and theoretical programming.

Abstract: The article is devoted to the use of digital educational resources in the process of teaching mathematics in a primary school. The possibility of using the ”Living Mathematics” electronic educational-methodical set with teaching guidelines on the topic ”Remarkable points of a triangle. Euler's line”. The article is addressed to teachers and students of pedagogical universities, methodologists, teachers of mathematics.

Abstract: Implementation of augmented reality session synchronization algorithm in mobile iOS applications. Algorithm allows to create augmented reality sessions with several participants for their joint interaction with the same virtual objects.