Abstract: “Technology of leading questions” as a teaching method is considered in the article. Substantial features of learning technology are disclosed. Pedagogical approaches to learning technology are considered. The components of learning technology as elements of the content structure are considered. The concepts: “leading question” and “technology leading questions” are defined. An example of the application of “technology leading questions” is proposed. The relevance of learning technology for the formation of skills to solve geometric problems on the proof is explained.

Abstract:

This paper considers problems associated with the documentation of employment process and management of employment records. Today, these tasks are solved through paper contracts and, in the Russian Federation, through «labor books». In this paper a software solution based on distributed ledger technology (blockchain) and smart contracts is proposed to replace the existing paper workflow.

Abstract:

Virtual odor is a new technology that allows the user to plunge the user completely into virtual reality. In the paper, we propose a method of using virtual odor in learning systems for criminalists. We also describe the scheme of this method.

Abstract: We have studied emotions in various aspects: philosophical, psychological and neurophysiological; taking them into account cognitive architecture has been described. Based on Lovheim “Emotion Cube”, “Wheel of emotions” by Plutchik, Tomkins “Theory of affects” and Marvin Minsky thinking model we describe usage of emotions as influence factors for computing processes. Also indicated the possibility of using emotions in intelligent question-answer systems.

Abstract:

The paper discusses the use of machine learning mechanisms, natural language analysis and intellectual search in the field of jurisprudence. The main expected results are the methodology for applying text-based analytics and semantic natural language processing (NLP) algorithms in knowledge management cases in different types of legal practice. The obtained results can be applied in the field of education and knowledge management in a wider context, since the study lies at the union of jurisprudence, mathematical and computer linguistics.

We describe a prototype of a multi-agent system of intellectual analysis of legal texts that is capable of identifying general dependencies on the existing database of legal documents, providing legal cases with similar topics, recommending the most likely outcomes of judicial review.

Abstract:

The paper presents the implementation of the patient medical digital passport, using distributed ledger for storing encrypted electronic health records, patient and medic digital entities and accesses for data. A system for the secure distributed storage of highly sensitive confidential medical data is described.

Abstract: Currently, the need for distributed ML training solutions in the world is increasing. However, existing tools, in particular TensorFlow Federated, are at the very beginning of their development, difficult to implement, and currently suitable exclusively for simulation on servers. For mobile devices, reliable approaches for this purpose do not exist. This article has designed and presented an approach to such distributed training of the ML-model on mobile devices, implemented on existing technologies. It is based on the concept of model personalization. In this approach, this concept is improved as a consequence of mitigating the identified drawbacks. The implementation process is structured so that at all stages of working with the ML-model use only one Swift programming language (Swift for TensorFlow and Core ML 3 are used), making this approach even more convenient and reliable due to the common code base.

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: I research and lecture in Cognitive Science where my particular interest is in emotions – neural networks modeling and applications – and animal and human learning.

Abstract: The article presents using the van Hiele theory of geometric thinking for the organization of mixed training of students of the pedagogical Department of the N.I. Lobachevsky Institute of mathematics and mechanics KFU on the basis of SPOC course «Elementary mathematics: Plane geometry». Training includes the use of various IT-techniques and tools that can improve the quality of learning and form the necessary professional competence of the future teacher of mathematics. The course implements the technology of project-modular and inverted learning.

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:

The article proposes a methodology related to the use of integrated project tasks in teaching mathematics, based on the practical application of the acquired knowledge in mathematical disciplines in conjunction with computer modeling and programming. Examples of specific integrated project tasks are presented.

Abstract: We described an evolution of thinking model in application with building intellectual question-answer system for automation processing user requests in natural language, starting with simple decision trees and finished with human thinking model. Every model has been developed, prototyped and tested. Experimental data and conclusions for every model provided.

Abstract:

The article is devoted to the creation of an effective solution for user segmentation. The article presents an analysis of existing user segmentation services, an analysis of approaches to user segmentation (ABCDx segmentation, demographic segmentation, segmentation based on a user journey map), an analysis of clustering algorithms (K-means, Mini-Batch K-means, DBSCAN, Agglomerative Clustering, Spectral Clustering). The study of these areas is aimed at creating a “flexible” segmentation solution that adapts to each user sample. Dispersion analysis (ANOVA test), analysis of clustering metrics is also used to assess the quality of user segmentation. With the help of these areas, an effective solution for user segmentation has been developed using advanced analytics and machine learning technology.

Abstract: A technology for creation of electronic educational materials is described. It allows to use the result electronic textbook as a part of smart-education environment. Developed algorithms make it possible to work with all kind of devices from PC to tablets without any limitations in functionality.

Abstract:

A service for generating and visualizing educational cards of mathematical concepts based on the ontology of school mathematics OntoMathEdu is presented. The main stages of collecting information for displaying the concept card are given. The developed service is used as a recommendation system in the distance education course of KFU "Technology for solving planimetric problems". Mathematical concepts located in the texts of lecture materials are enriched with links to the corresponding concept card on the service.

Abstract:

The video editing process involves numerous labor-intensive operations for sorting and preparing footages, requiring significant time investment. This article describes the development of a software solution that uses machine learning technology to automate these processes.

The primary focus is on creating a system capable of classifying and sorting media files according to the screenplay text, thereby increasing the efficiency of material preparation for editing. The system includes modules for speech recognition, audio and video classification, and algorithms for determining screenplay compliance.

Testing showed that the proposed system correctly classifies media files in most cases, significantly reducing rough-cut editing time.

Abstract: There are various approaches for creating artificial intelligence in games, and each has both advantages and disadvantages. This study describes an authoring implementation of the NPC behavior task using machine learning algorithms that will be associated with the Unity environment in real time. This approach can be used in game development.

Abstract:

The enrichment of educational texts with semantic content (in particular, adding hyperlinks to the pages of the service that displays detailed information about concepts in the text) helps to increase the efficiency of students' assimilation of the material. The existing methods of semantic markup of educational texts do not take into account the structural features of such documents, which leads to excessive recognition of concepts. This article describes the development of the method of automatic annotation of mathematical concepts in educational mathematical texts by adding functionality to account for the structure of an educational document. The main purpose of the method is to process educational materials of the distance education course "Technology for solving planimetric problems". Following a single template when creating course pages allows you to apply an analysis of the web page markup and keywords used by the course creators. The main task in this process is to determine the type of table cell containing text fragments of educational materials. In accordance with the recommendations of the course creators, definitions should be highlighted in the cells containing the task statement, as well as in those blocks where the input data of the task is indicated. The type of table cells is determined by analyzing their attributes and searching for keywords in their contents. This limitation of recognizable text fragments will improve the student's perception of the course pages and improve the quality of learning.