Computational nanotechnology

The article describes a technique for constructing a 3D model of an object based on the resulting images of an object using the Python programming language. As part of the study, an overview of existing solutions and an analysis of the use of algorithms for constructing three-dimensional models were performed. As a result of the work done, software was created that allows you to create a three-dimensional model based on several presented images. The scope of this work is the analysis of an object using a three-dimensional model, as well as the use of three-dimensional terrain models.

The article is devoted to the development of a visual odometry model based on sensors of an inertial measuring device and the analysis of a video stream arriving in real time. Modeling is based on the analysis and evaluation of methods for measuring the correct coordinates of a moving object, systems for estimating the movement of an object in three-dimensional space, algorithms at intermediate stages of image processing, principles for selecting special points on the frame and optical flow for selected points.

In the context of intensive development of information technology and increasing complexity of software products, the importance of effective interaction between members of work teams when implementing complex software solutions, such as enterprise automation systems based on the 1C platform, is increasing. This article is devoted to the study and modeling of interaction processes between members of project teams aimed at increasing the effectiveness of their joint activities during the implementation of projects for the implementation of corporate information systems. As part of the study, existing approaches and methods for organizing teamwork, as well as software systems that provide monitoring and management of collaboration of specialists, were analyzed. Particular attention is paid to considering the specifics of interaction when implementing 1C systems, characterized by a high degree of adaptability and variability depending on the characteristics of a particular enterprise. Research materials and methods include studying scientific literature on the issues of managing project teams, analyzing statistical data on the results of implementing corporate information systems in various sectors of the economy, as well as conducting interviews with managers and participants in 1C implementation projects at medium and large businesses. As part of this study, methods for modeling the work of a project team were studied. In the process of work, the analysis of her activities (business and interpersonal) was taken into account. In the course of the work, the conflict phase of team development was identified, and a model of effective motivation was created. For this purpose, game theory tools were used. As a result of the study, key factors were identified that influence the effectiveness of interaction between project team members, among which are a clear distribution of roles and responsibilities, well-established communications, and the use of modern collaboration and task management tools. Based on the data obtained, the authors proposed a conceptual model for organizing effective interaction between participants in 1C implementation projects, taking into account the specifics of this subject area and aimed at minimizing risks and improving the quality of the results of project activities.

The relevance of the study is to identify the accuracy of the estimate obtained by the A2C algorithm, as well as the need for verification of reinforcement learning when working with optimization of economic processes. The purpose of the study was to analyze the effectiveness of the A2C algorithm, along with the specifics of its implementation, in solving optimization economic problems. The tasks considered were maximizing consumption in the Solow, Romer and Schumpeterian models of endogenous economic growth, and maximizing per capita income in the latter two, according to the consumption rate (in the latter two – saving rate) and the share of scientists in the economy, respectively. The results showed that for deterministic models (Solow model, Romer model), the variance of the parameter estimate is minimal and the average differs from the value obtained analytically by no more than a thousandth part with a sufficiently high number of time periods in the model. Nevertheless, in stochastic models (the Schumpeterian model), firstly, a high number of time periods in the model is required to match the estimate to the value obtained analytically, and secondly, the estimate obtained in this way, although biased by no more than a thousandth of a fraction, has a high variance.

The study suggests the use of RFID technology to effectively manage food consumption, as well as reduce the volume of unused products. The system includes special readers for automatic receipt and transmission of information about products. Users can monitor the expiration date and receive information through the web application, which also sends notifications about the approaching expiration date, contributing to a more rational use of products.

This article unveils EMICA, a Python-based software tool revolutionizing electron microscopy image processing for amorphous alloys. EMICA addresses the unique challenges posed by these materials, which lack long-range order, by providing specialized capabilities for cluster analysis and spatial pattern recognition. This research explored software tool development and application through illustrative examples, answering the key question of how they enhance amorphous alloy analysis. By integrating advanced image processing techniques and algorithms, EMICA uncovers hidden patterns, offering quantitative insights into cluster distributions. The key message emphasizes the application’s transformative impact on material science research, providing a specialized solution for electron microscopy image analysis in the amorphous alloy domain. Our key findings, presented through real-world examples and case studies, attest to the efficacy of the software in revealing nuanced details of amorphous alloy structures. From identifying subtle variations in atomic configurations to quantifying cluster distributions, EMICA represents a significant leap forward in the field of advanced electron microscopy image processing, contributing significantly to the advancement of this domain.

Within the framework of the of density functionality theory and the pseudopotential method, the atomic and electronic structure of the two-dimensional Li–Si and Be–Si systems forming on the Si (100) surface is calculated, with a metal thickness of one to three monolayers (ML). At the first ML, the formation of ordered silicide wetting layer of Li (with atoms embedded inside the top layer Si) and Be (with atoms embedded between the top two Si layers) was detected. At 2 ML, the systems are modified: Li atoms occupy positions between the top two Si layers, and Be atoms rise at positions above the top Si layer. After that, with a coating thickness of 3 ML, in the case of Li, a continuous disordered wetting layer is formed, and in the case of Be, a wetting layer in the form of disordered chains along the length. At 1 ML, an energy gap appears in the electronic structure of the studied systems in the density of electronic states near the Fermi level, the width of which is 1.02 eV and 0.36 eV, respectively, for Li-Si and Be-Si systems. Then the gap disappears, first for the lithium system (at 2 ML), and then, for the beryllium system (at 3 ML).

This study investigates the application of neural networks in the task of classifying audio signals into ten different genres. The peculiarities of processing audio signals in the digital environment are examined, along with the relationship between Fourier transformation and spectrograms, and the characteristics of audio signals. Neural network training was conducted using the GTZAN dataset, which contains 1000 compositions. Four comparable datasets were formed based on this dataset, and the performance of three neural network architectures – convolutional, recurrent, and multilayer perceptron – was evaluated on each of them. The practical significance of this work lies in the possibility of forming musical recommendations and organizing music. The goal of the study is to develop a classifier that could accurately determine the probability of a composition belonging to one of the ten genres.

Machine learning, and neural networks in particular, are having a huge impact on business and marketing by providing convenient tools for analytics and customer feedback. The article proposes an intelligent analysis of customer feedback based on the use of a modified seq2seq deep learning model. Since the basic seq2seq model has a significant disadvantage – the inability to concentrate on the main parts of the input sequence, the results of machine learning may give an inadequate assessment of customer feedback. This disadvantage is eliminated by means of a model proposed in the work called the “attention mechanism”. The model formed the basis for the development of a web application that solves the problem of flexible interaction with customers by parsing new reviews, analyzing them and generating a response to a review using a neural network.

Nowadays programming is an indispensable part of modern life. It is the foundation for the development and implementation of new technologies and solutions in various fields of human activity: personal to professional. Recently, there has been significant progress in the development of information technologies due to the constant scientific and technological advances around the world. The purpose of this paper is to analyze the current situation as well as trends in the development of software development. The work uses theoretical methods of research, such as analysis, synthesis and generalization. Because of this work, the author has identified the main trends and tendencies observed in the information technology industry. Based on the results obtained, the author makes conclusions about how the software development industry will develop and what technologies will have the greatest impact in the future. The scientific value of the current work consists in the formation and systematization of the most important trends and prospects of programming development. The materials of the work can be useful for modern software developers, architects and project managers in technology companies, allowing them to identify the most promising directions in the aspect of development of their competencies.

In the first part of the article discusses fundamental aspects of the pulsed tunneling effect as a unified mechanism for describing tunneling phenomena in various fields of physics are considered. The main provisions of the pulsed tunneling theory developed by Keldysh are analyzed. The features of the effect’s implementation in optics, nanoelectronics, perovskites and other materials are examined. The role of coherent radiation is shown. The prospects of regulating material properties and observing non-standard phenomena due to PTE are discussed. In the second part of the article discusses examines the subtleties of the pulsed tunneling effect as a fundamental mechanism of interaction of radiation with matter. The advantages of the ITE compared to the standard quantum tunneling effect are analyzed. Particular attention is paid to the role of radiation coherence and unidirectional polarization during pulsed exposure. The features of the manifestation of effects in optics, nanotechnology and biology are considered. The prospects for using ITEs to create new functional materials and effective technologies are shown.

This study focuses on investigating the potential of modified ceramic technology methods for producing composition materials with nano-level heterogeneity, approximating the properties of functional ceramics (FC) obtained through helio-technology. Three different powder synthesis methods were utilized: oxide method, ceramic technology, and sol-gel technology. X-ray diffraction and electron microscopy analyses were employed to compare the microstructure of powders obtained by these methods with samples synthesized using helio-technology. The results revealed that powders obtained through modified ceramic technology methods exhibited a more homogeneous structure and smaller particle size compared to those obtained through helio-technology. Nano-sized, metastable, and amorphous phases formed at the boundaries of such powders are considered responsible for the generation of pulsed infrared radiation. These findings have significant practical implications in various fields that require composition materials with controlled properties and the ability to generate pulsed infrared radiation.