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  • Features of the arrangement of the abutments of the projected driveways of industrial enterprises to the existing landscaping

    The paper considers the problem of the arrangement of the abutments of newly erected driveways and roads of agricultural production enterprises to existing roads and driveways. When connecting the "pies" of the roadways of the projected driveways with the existing landscaping, it is necessary to solve the problem of preventing cracking in the coating at the places of the thickness difference of the structural layers. In the article, this problem is solved both from the technical side, by ensuring the joint work of the new and existing road structure, and from the normative one by assigning the projected passage to the IVB category road, in accordance with SP 37.13330.2012, which allows the construction of a road with curbs without curbs and, as a consequence, without storm sewers and sewage treatment plants.

    Keywords: road network, cadastral boundaries, the design of the widening of the passage, the technical solution of the junction of roads, transverse profile

  • Technical and economic analysis of the conversion of a historic dam into a small hydropower plant

    The paper considers the opportunities and obstacles to the integration of renewable energy sources (RES) in megacities on the example of Moscow. The paper analyzes the applied RES-based generation technologies, taking into account their applicability in large cities. Special attention was paid to the conversion of unused historical dams into small hydroelectric power plants (SHPP) as an integration of RES in megacities. Based on the results of the technical and economic analysis, it was found that the conversion of an unused dam on the Yauza River into a SHPP is justified.

    Keywords: small hydropower, unused dam, megacity, renewable energy integration

  • The use of universal adversarial attacks in the tasks of increasing the effectiveness of protection systems against robots and spam

    This article discusses the use of universal adversarial as well as to improve the effectiveness of protection systems against robots and spam. In particular, the key features that need to be taken into account to ensure an optimal level of protection against robots and spam are considered. It is also discussed why modern methods of protection are ineffective, and how the use of universal adversarial attacks can help eliminate existing shortcomings. The purpose of this article is to propose new approaches and methods of protection that can improve the effectiveness and stability of protection systems against robots and spam.

    Keywords: machine learning, clustering, data recognition, library Nanonets, library Tesseract

  • Approximate mathematical model and finite element simulation of air flow in an expanding truncated cone

    An original approach to describe airflow in the thin conic diffusor is suggested. It is based on approximate analytic solution of continuity equation. In addition simplified model of turbulence is combined. Reliability of derived formula is confirmed by comparison with finite-element solution for designed experimental setup. The elaboration is intended to direct computer simulation of multiphase flow.

    Keywords: dust-air mixture, aspiration systems, turbulence, finite element modeling, separation diffuser, digital twin

  • Indirect determination of the dispersity of atomized fuel from the geometry of the wetting spot zone

    A program for computer simulation of atomization of liquid fuels has been developed. A special calibrating experiment was carried out in a gravitational field. Verification of the computer model with experimental data is carried out, the correctness of simulation modeling is determined by the convergence of the results of static generalization. Tests of a model sample of the burner device were carried out, confirming the adequacy of computer simulation.

    Keywords: burner, atomization of liquid fuels, mathematical modeling, fuel jet dispersion dynamics, nozzle

  • Stock market forecasting model based on neural networks

    The article is devoted to the consideration of topical issues related to the study of the possibility of forecasting the dynamics of stock markets based on neural network models of machine learning. The prospects of applying the neural network approach to building investment forecasts are highlighted. To solve the problem of predicting the dynamics of changes in the value of securities, the problems of training a model on data presented in the form of time series are considered and an approach to the transformation of training data is considered. The method of recursive exclusion of features is described, which is used to identify the most significant parameters that affect price changes in the stock market. An experimental comparison of a number of neural networks was carried out in order to identify the most effective approach to solving the problem of forecasting market dynamics. As a separate example, the implementation of regression based on a radial-basis neural network was considered and an assessment of the quality of the model was presented.

    Keywords: stock market, forecast, daily slice, shares, neural network, machine learning, activation function, radial basis function, cross-validation, time series

  • The use of the "Quality Index" in the assessment of construction and installation works

    The problem of quality in construction and installation works at intermediate stages is being discussed. The role of technical supervision in the construction process is outlined. A proposed indicator, the "Quality Index," is presented for consideration, which reflects not only the quality of the works but also the effectiveness of the technical supervisor's work during the construction process.

    Keywords: quality, construction quality, construction quality index, quality coefficient, regulations, technical supervisor engineer

  • Graph neural networks and XANES spectroscopy for investigation of the structure of copper centers in Cu-MOR

    In this paper, the possibility of applying graph neural networks (NN) to study the structure of copper centers of zeolites is considered. The dataset used for NN training was prepared using the FDMNES software based on the finite difference method and included more than 2100 Cu K-XANES spectra for Cu-MOR. The performed study demonstrated the capability of graph neural networks to reproduce the Cu K-XANES spectrum corresponding to a particular model of the copper center in the zeolite framework.

    Keywords: zeolite, mordenite, atomic structure, XANES, machine learning, graph neural networks

  • Preservation of greenery during construction

    The issues of preserving existing green spaces and other elements of the natural landscape during new construction are considered. Methods for preserving perennial plantings throughout the entire course of construction are proposed. If it is impossible to save the tree at the construction site, a method of transplanting it to another place is proposed. It is proposed at the stage of design and survey work to identify healthy trees that do not grow on the site allocated for a building (structure) under construction. Then solve the problem of locating the object on the ground in such a way as to preserve healthy perennial trees as much as possible. To do this, it is necessary to carry out the removal of the object to the area, moving it as far as possible from healthy trees. The distance required to protect the tree from external influences during work is equal to the projection of the crown on the ground plus 1.5 m. At this distance, it is recommended to make stationary fences for each tree. A tree transplantation scheme and a method for calculating its weight for the selection of equipment for digging and transportation have been developed.

    Keywords: landscaping, construction, tree, tree transplanting, asphalting

  • Information system for forecasting the collection of payments in the post offices of the Russian Post using machine learning

    This article discusses the forecasting of the collection of payments in post offices, taking into account seasonality and the use of machine learning. An algorithm for constructing a calculation model has been developed, which provides an opportunity for analysts of the Russian Post to make a monthly forecast of the collection of payments for each UFPS (Federal Postal Administration), taking into account seasonality. This model allows you to identify deviations from the norm in matters related to the collection of payments and more accurately adjust the increase in tariffs for services. The SSA algorithm is considered, which consists of 4 steps: embedding, singular decomposition, grouping, diagonal averaging. This information system is implemented in the form of a website using a framework ASP.NET Core and libraries for machine learning ML.NET . Then the forecast is evaluated using various methods.

    Keywords: mathematical modeling, seasonally adjusted forecasting, collection of payments, machine learning, neural network

  • Development of a recommendation system for training selection

    The article discusses the methods and approaches developed by the authors for the recommendation system, which are aimed at improving the quality of rehabilitation of the patient during respiratory training. To describe the training, we developed our own language for a specific subject area, as well as its grammar and syntax analyzer. Thanks to this language, it is possible to build a devereve describing a specific patient's training. Two main methods considered in the article are applied to the resulting tree: "A method for analyzing problem areas during training by patients" and "A method for fuzzy search of similar areas in training". With the help of these methods, it is proposed to analyze the problem areas of patients' training during rehabilitation and look for similar difficult areas of the patient to select similar exercises in order to maintain the level of diversity of tasks and involve the patient in the process.

    Keywords: Recommendation system, learning management system, rehabilitation, medicine, respiratory training, marker system, domain-specific language, Levenshtein distance

  • On the issue of the reconstruction of the A-2 station in the context of the development of the North–South transport corridor

    The article deals with the issue of the reconstruction of the A-2 station in the context of the development of the North–South transport corridor. The relevance of the topic lies in the need to master the growing volumes of transportation from Russia to the countries of Southeast Asia and back in connection with the current reorientation of the main export cargo flow and economic ties of Russia. The analysis of the existing volumes of work of the station is carried out. To develop proposals, an analysis of the volume of work of the station was carried out, according to which there was a decline in production over the previous period. Measures are proposed for the effective development of the expected cargo flow. Statistical modeling methods, queuing systems theory and feasibility studies were used as methods. As a result, the proposals made are aimed at implementing the effective operation of the A-2 station. The reconstruction of the station makes it possible to ensure the development of increased cargo volumes and thereby receive additional income.

    Keywords: relevance, transport corridor, station, goal, analysis, cargo turnover, volume of work, forecast, activities, expected effect

  • Blockchain as a service for protecting information about the authenticity of educational diplomas

    The problem of fake diplomas of education causes alarm and concern to society. In the digital age, falsification has reached great proportions. In this regard, a mechanism for recording and confirming the authenticity of diplomas using technology is proposed. A sector-token method of accessing a blockchain record is proposed. The recording technology and the blockchain formation model are shown. The proposed technology guarantees that the diplomas are genuine, protected from forgery, belong to the specialists who received them.

    Keywords: blockchain, data protection, diploma forgery, educational institution, authentication

  • Formation of Island Nanostructures by Sublimation Epitaxy in Electronic Technology

    The possibilities of a little-studied method for obtaining nanosized materials of electronic engineering with a given substructure, the zone sublimation epitaxy (ZSE) method, are discussed. In the work, it is combined with the method of gradient liquid phase epitaxy (GLE). A specific feature is mass transfer in a two-phase medium (a solid substrate and an inert gas phase acting as a transport medium) with preliminary deposition of a matrix layer formed from the melt. A feature of the sublimation process in the study was the crystallization of low-melting iron-silicon eutectic. A mathematical model of the process was proposed and compared with the experimental results. Island structures of the composition silicon (more than 90%), iron (up to 8%) and chromium (about 1.5%) have been obtained. Their parameters and size distribution were studied. A Solver-HV scanning probe microscope and a Quanta-200 scanning electron microscope were used. The study shows that the use of sublimation transfer transients makes it possible to reproducibly form doped silicon nanolayers and transform them into regular mesostructures.

    Keywords: microsize growth cell method, zone sublimation epitaxy, gradient liquid phase epitaxy, island nanostructures

  • The method of selecting configurable hyperparameters of the intelligent classifier of unstructured text data according to the degree of confidentiality based on the hierarchy analysis method

    A structural model of an intelligent classifier of unstructured textual data according to the degree of confidentiality is presented, which is a two-level cascading ensemble of classifier models. The meta-model of a fully connected neural network architecture, which has the greatest impact on the classification efficiency, is highlighted. The multi-criteria task of configuring the intelligent classifier is decomposed into the task of selecting configurable hyperparameters of the meta-model and the task of selecting their values. Taking into account the selected hyperparameters of the neural network meta-model, the multi-criteria task of selecting hyperparameters to be configured is presented in the form of a hierarchy that includes the goal, criteria and alternatives. A method for selecting configurable hyperparameters of an intelligent classifier of unstructured text data by the degree of confidentiality based on the hierarchy analysis method has been developed.

    Keywords: DLP system, unstructured text data, intelligent classifier, hyperparameters, hierarchy analysis method