Attempts were made in the present study to design and develop skeletally modified ether linked tetraglycidyl epoxy resin (TGBAPSB), which is subsequently reinforced with different weight percentages of amine functionalized mullite fiber (F-MF). The F-MF was synthesized by reacting mullite fiber with 3-aminopropyltriethoxysilane (APTES) as coupling agent and the F-MF structure was confirmed by FT-IR. TGBAPSB reinforced with F-MF formulation was cured with 4,4’-diamino diphenyl methane (DDM) to obtain nanocomposite. The surface morphology of TGBAPSB-F-MF epoxy nanocomposites was investigated by XRD, SEM and AFM studies. From the study, it follows that these nanocomposite materials offer enhancement in mechanical, thermal, thermo-mechanical, dielectric properties compared to neat (TGBAPSB) epoxy matrix. Hence we recommend these nanocomposites for a possible use in advanced engineering applications that require both toughness and stiffness.

The article addresses the issue of educational development policy in Ukraine: the main trends and ways, means, technologies of their implementation. It has been observed that educational policy is developing and changing under the influence of such factors as Russia’s military actions against our country, European integration and globalisation. It has been taken into account that globalisation trends in the world integration, according to which globalisation processes should be reflected not only in the foreign economic, political or technological spheres, but also, as a consequence, in the development of technologies for training future teachers. Integration of digital technologies in the educational process is one of the key tendencies in the modern educational policy in Ukraine. The characteristics of the most used technologies of augmented reality in the modern school of Ukraine have been outlined. The algorithm for displaying generalized information about a particular application was proposed, namely: payment, accessibility, language, system requirements; learning opportunities; practical value; website; video about the application. The model of the formation of future teachers’ skills to use augmented reality technologies in the process of natural sciences studying has been proposed. We consider it as a component of a holistic system of future teachers’ professional training. The conceptual basis for the development of the model is a multi-subject educational paradigm, which is considered to be open, self-developing and self-organizing, causing a fundamental change in the behavior and relationships of the educational process participants. The proposed model is implemented in the authors’ methodological system, which ensures the interconnected activities of all participants in the educational process. Its systemic factor is the goal of improving the quality of the future natural sciences teachers’ professional training by developing their skills in using AR technology. The end result is an increase in the level of future natural sciences teachers’ readiness to use AR technology in their professional activities.

This study aims to explore the design and application of a learning achievement evaluation model, in order to improve the quality of teaching in the field of education and promote student development. This article starts with the importance of constructing a learning effectiveness evaluation model, and then clarifies the basic concepts and related theories of learning effectiveness evaluation, providing theoretical support for subsequent model design. In the model design section of learning effectiveness evaluation, propose the model design principles, indicator selection, and construction process to ensure the accuracy and comparability of the evaluation model construction. In the application and evaluation section of the learning effectiveness evaluation model, the application and evaluation methods of the main models in practical teaching were explored. Finally, the issues that need to be noted in the design process of the evaluation model were proposed in order to design a more high-quality evaluation system and promote the improvement of education quality.

The growth of mobile Internet has facilitated access to information by minimizing geographical barriers. For this reason, this paper forecasts the number of users, incomes, and traffic for operators with the most significant penetration in the mobile internet market in Colombia to analyze their market growth. For the forecast, the convolutional neural network (CNN) technique is used, combined with the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit (GRU) techniques. The CNN training data corresponds to the last twelve years. The results currently show a high concentration in the market since a company has a large part of the market; however, the forecasts show a decrease in its users and revenues and the growth of part of the competition. It is also concluded that the technique with the most precision in the forecasts is CNN-GRU.