In the article the avatar-based learning and teaching (A-BL&T) as a concept of control and managing knowledge in modern socio-economic conditions is proposed to use for assessment a university's economic efficiency. It is shown that all elements, methods and techniques (tools) do not operate in isolation, but rather are interrelated, complementing each other. All of them are used in the process of management and, in a combination, are powerful tools for increasing efficiency of management. Based on the example of avatar-based learning and teaching in Russian universities as modern educational environments, a conceptual model, methodology, and methods have been obtained for the automation of planning and calculation of the academic load in the university.

Automatic image recognition is very useful in bioinformatics. This article presents a novel technique to recognize the characters in the number plate automatically by using connected component analysis (CCA), artificial neural network (ANN) and neural natural network (Triple N). The preprocessing steps, Sobel edge detection technique and CCA are applied to the captured image of the vehicle to obtain character images. ANN technique can be used over these images to recognize the characters of the image in bioinformatics. The preprocessing steps are used to remove the noise and to enhance the image for recognizing the characters effectively. After performing the preprocessing steps, the edge detection technique and CCA are carried out to separate the character images from the whole image which can be recognized using ANN. These text characters can be compared with database to find authentication of vehicle, identifying the owner of the vehicle, penalty bill generation, etc.

Purpose of the study: The purpose of this work is to consider the possibilities of hermeneutics in developing the skill of understanding a musical text as one of the main mental abilities of musician-performers. Methodology: The study is based on the method of hermeneutics, the method of analyzing a musical text, which is widely used in the humanities and social sciences in general and plays an essential role in art criticism. Unlike other methods, text analysis uses the point of view of the author of the text. Interpretative and content analysis are the two primary forms of textual analysis of cultural artifacts. Interpreting textual analysis seeks to go beyond the surface of the meaning and explore the hidden "message" of the author. Main Findings: The main findings of the study are that the role of musical hermeneutics is important in the professional training of contemporary performers in connection with the need to develop their ability to understand a musical text and form a culture of interpretation. Applications of this study: This research can be used in musicological analysis and the process of professional education of musician-performers and theorists. The novelty of the work consists in proving the effectiveness of the method of musical hermeneutics in the formation of a culture of interpretation in performers. Novelty/Originality of this study: The method turned out to be effective for not only the theory of literature, hermeneutics, and semiotics, but also for musicology and the work of composers and performers directly working with intertexts.

This chapter discusses issues related to managing the avatar-based supply chains as expert knowledge for smart solutions in creating sustainable urban systems. Avatar-based supply chains as expert knowledge is a new term that describes the planning, search, production, distribution, and delivery of Mkrttchian's digital avatars from the place of origin to consumption. These supply chains are very different from traditional ones because they relate to a specific product-expert knowledge, which is created through electronic data distributed on the internet between business partners and value-added service providers operating in a general digital economy paradigm using blockchain technologies. This chapter focuses on the analysis of business relations and this integration into sustainable urban systems.

Automatic image recognition is very useful in bioinformatics. This article presents a novel technique to recognize the characters in the number plate automatically by using connected component analysis (CCA), artificial neural network (ANN) and neural natural network (Triple N). The preprocessing steps, Sobel edge detection technique and CCA are applied to the captured image of the vehicle to obtain character images. ANN technique can be used over these images to recognize the characters of the image in bioinformatics. The preprocessing steps are used to remove the noise and to enhance the image for recognizing the characters effectively. After performing the preprocessing steps, the edge detection technique and CCA are carried out to separate the character images from the whole image which can be recognized using ANN. These text characters can be compared with database to find authentication of vehicle, identifying the owner of the vehicle, penalty bill generation, etc.