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  • Reviews, suggestions and discussions

  • Laser technologies in the construction industry: advantages and disadvantages

    The use of innovative technologies in construction is necessary at all stages of the production cycle from design to operation, reconstruction and overhaul of buildings and structures. One of the leading technologies used to collect and process data on construction sites, sites and territories is laser three-dimensional scanning. In this paper, the features of the use of three-dimensional laser scanning in the construction industry are considered, the advantages and disadvantages of this research method are determined, the stages and principles of this type of measuring design work on the ground are identified.

    Keywords: cost management, laser three-dimensional scanning, point cloud, BIM technologies

  • An overview of machine learning-based techniques for detecting outliers in data

    Outlier detection is an important area of data research in various fields. The aim of the study is to provide a non-exhaustive overview of the features of using methods for detecting outliers in data based on various machine learning techniques: supervised, unsupervised, semi-supervised. The article outlines the features of the application of certain methods, their advantages and limitations. It has been established that there is no universal method for detecting outliers suitable for various data, therefore, the choice of a particular method for the implementation of research should be made based on an analysis of the advantages and limitations inherent in the chosen method, with the obligatory consideration of the capabilities of the available computing power and the characteristics of the available data, in including those including their classification into outliers and normal data, as well as their volume.

    Keywords: outliers, machine learning, outlier detection, data analysis, data mining, big data, principal component analysis, regression, isolating forest, support vector machine

  • Analysis of the transport and logistics system of rescue operations using mobile equipment during earthquakes and man-made disasters

    Elimination of the consequences of emergencies during rescue operations will be successful with the use of reliable modular lifting equipment. The proposed concept of the mobile equipment system contributes to the use of layer-by-layer dismantling of the rubble of destroyed multi-storey buildings and structures. The main structural elements of the system of mobile lifting equipment are presented.

    Keywords: earthquakes and disasters, mobile equipment, lifting device, time minimization, modular device

  • Technologies of green facades and green roofs in the construction of schools

    This article examines and raises the issues of developing a favorable atmosphere and environment for students on the example of the use of green roofs and facades in the construction of schools. Foreign and domestic rating systems for green standards, criteria for their certification are highlighted, as well as the heat-shielding properties of these structures, their structure, economic indicator and implementation examples are studied in detail. A specific example of the use of a green roof and facade in the construction of a school in France is presented. The tools used to introduce green school building with state support were also given in this article.

    Keywords: green roofs, green facade, ecological building, green standards, environment, materials, green technologies, green schools

  • Chinese inventions on the field of nonisocyanate polyurethane

    For last 10 years creating of new patents in the field of nonisocyanate polyurethane have passaged Chinese inventors. Chinese inventions in the field of NIPU consist about 15% all such inventions, but that are not pioneer ones, especially for foam application.

    Keywords: patents, nonisocyanate polyurethanes, oligomeric cyclocarbonates

  • Technical science. Informatics, computer facilities and management

  • Modernization of the air blower control system

    Models of open-loop and closed-loop systems for automatic control of air supply to a steam boiler are constructed. An open-loop system is modeled and, on its basis, a closed-loop system with a PI controller tuned to the optimum modulo is developed. The introduction of a frequency converter into the control system for more economical and gentle operation of the fan electric drive is considered. The developed system consists of models of a controller, a frequency converter, an asynchronous motor and a blower fan. The simulation results are presented, demonstrating the operability of the resulting system in compliance with the requirements for stability and speed. The modernized closed system has a number of advantages over the existing open one, and the described method of its construction can be applied when implemented at enterprises using air blowers.

    Keywords: automatic pressure control system, automatic control system, closed system, open system, PI controller, modular optimum

  • Vulnerability analysis in data security systems

    The article is a review work on the methods and technologies used in the analysis of vulnerabilities in information systems. The article describes the main steps in conducting a vulnerability analysis, such as collecting information about the system, scanning the system for vulnerabilities, and analyzing the scan results. It also discusses how to protect against vulnerabilities, such as regularly updating software, conducting vulnerability analysis, and developing a data security strategy.

    Keywords: vulnerability analysis, data security, information security threats, attack protection, information security, computer security, security risk, network vulnerability, security system, protection

  • Approach for implementation of stream cipher based on fuzzy pseudo-random secquences generator

    An approach for cosntruction of stream ciphers based on new type of cipher gamma generators with a non-linear (fuzzy) shift register selection function is proposed. The best configuration of generator is selected for generating a gamma whose properties are closest to white noise. It is shown that the proposed approach makes it possible to generate a gamma sequence with a quality that exceeds a number of other classical generators.

    Keywords: cryptography, stream cipher, gamma, PNSG, random test, fuzzy logic,membership function, linguistic variable, defuzzification, linear feedback shift register

  • 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

  • Developing the associative file protection application

    In today's information environment, characterized by the increasing digitalization of various aspects of daily life, information security is of paramount importance. Many types of personal information, including identity, financial and medical records, are digitally stored. Organizations need to protect their intellectual assets, sensitive data and business information from competitors and insider threats. The synergistic approach of combining cryptography and steganography provides increased sophistication in analyzing transmitted data and reduces its vulnerability to attacks based on statistical analysis and other pattern detection techniques. Associative Steganography is a methodology that integrates the basic principles of steganography and cryptography to provide strong data protection. The development of a software application designed for associative file protection can be applied in a wide range of areas and has significant potential in the context of information security. In this article the prerequisites for creating this application are discussed, the program design of the application is described using UML (Unified Modeling Language) and aspects of its implementation are analyzed. In addition, the results of testing the application are investigated and further prospects for the development of associative steganography are proposed.

    Keywords: associative steganography, stego messaging, stego resistance, cryptography, information security, Unified Modeling Language, .NET Framework runtime, Windows Presentation Foundation, DeflateStream, BrotliStream, MemoryStream, parallel programming

  • Development of a malware detection method using a system call graph using machine learning

    This article is devoted to solving the problem of research and detection of malware. The method implemented in the work allows you to dynamically detect malware for Android using system call graphs using graph neural networks. The objective of this work is to create a computer model for a method designed to detect and investigate malware. Research on this topic is important in mathematical and software modeling, as well as in the application of system call control algorithms on Android devices. The originality of this direction lies in the constant improvement of approaches in the fight against malware, as well as limited information on the use of computer simulation to study such phenomena and features in the world.

    Keywords: system calls, android, virus, malware, neural networks, artificial intelligence, fuzzy logic

  • 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

  • Data imputation by statistical modeling methods

    One of the tasks of data preprocessing is the task of eliminating gaps in the data, i.e. imputation task. The paper proposes algorithms for filling gaps in data based on the method of statistical simulation. The proposed gap filling algorithms include the stages of clustering data by a set of features, classifying an object with a gap, constructing a distribution function for a feature that has gaps for each cluster, recovering missing values ​​using the inverse function method. Computational experiments were carried out on the basis of statistical data on socio-economic indicators for the constituent entities of the Russian Federation for 2022. An analysis of the properties of the proposed imputation algorithms is carried out in comparison with known methods. The efficiency of the proposed algorithms is shown.

    Keywords: imputation algorithm, data gaps, statistical modeling, inverse function method, data simulation

  • Calculation of optimal DCS parameters using graph theory methods

    The article discusses the use of graph theory to calculate the location of elements and ways of laying information cables in a distributed control system. It describes how the use of graph theory can help improve system performance, reduce maintenance costs, and increase reliability and security. The article presents the general principles of using graph theory to solve problems related to the location of elements and paths for laying information cables in distributed control systems. The authors conclude that the use of graph theory is a powerful tool for solving problems associated with distributed control systems, and can be effectively applied to improve the efficiency of the system, reduce costs and increase reliability and security.

    Keywords: graph theory, distributed control system, Python, Matplotlib, production process optimization, automatic analysis, control system, data cable, automation

  • The method for the technical and economic assessment of options for building an organizational and technical system of the "cyberpolygon" class

    The article is devoted to the study of problematic issues of the formation of organizational and technical systems of the "cyberpolygons" class using the original methodological apparatus for the feasibility study of system engineering solutions for their construction. The features of existing approaches to the justification of system engineering solutions for the construction of organizational and technical systems, information technology and technical systems are considered. Directions for their development are proposed, taking into account the dynamics of the phased creation and modernization of organizational and technical systems with simultaneously developing infrastructure projects and solutions. Formal aspects in the methodological apparatus are reflected in the change in the composition of the functional components in the conceptual and analytical models, the corresponding formal descriptions of their relationships and characteristics, as well as in the modification of the procedures for the technical and economic assessment of options for building a cyberpolygon. The method of technical and economic evaluation of options for constructing a cyberpolygon proposed in this study makes it possible to rank alternative options for the infrastructures of the created cyberpolygon according to the value of their technical and economic efficiency and to select the rational one from them.

    Keywords: information security, infrastructure, cyberpolygon, feasibility study, means of protection

  • Application and comparison of evolutionary algorithms in the framework of the problem of reinforcement learning for unstable systems

    The aim of this work is the implementation and comparison of genetic algorithms in the framework of the problem of reinforcement learning for the control of unstable systems. The unstable system will be the CartPole Open AI GYM object, which simulates the balancing of a rod hinged on a cart that moves left and right. The goal is to keep the pole in a vertical position for as long as possible. The control of this object is implemented using two learning methods: the neuroevolutionary algorithm (NEAT) and the multilayer perceptron using genetic algorithms (DEAP).

    Keywords: machine learning, non-revolutionary algorithms, genetic algorithms, reinforcement learning, neural networks

  • Method of normalization of fields of external sources of the MITRE CTI cyberattack data repository

    The growing complexity of industrial systems significantly increases the surface of possible cyber attacks, and therefore requires reliable methods for assessing the security of infrastructure. Modern methods of security assessment rely on working with a large amount of data, the presentation of which is often not standardized. One of these sources is the MITRE ATT&CK knowledge base, which contains information about attacking techniques in a format that allows you to interact with it programmatically. This work is aimed at solving the problem of normalizing the fields of external sources describing the attacking technique in order to increase the efficiency of working with the repository described above. The method proposed in this paper is based on the possibility of the specification of the STIX language used to describe the data presented in MITRE ATT&CK to expand and use open dictionaries. The development of the proposed method was based on data on the attacking techniques of the Enterprise matrix, as the most complete among all domains of the ATT&CK knowledge base, however, the proposed method is independent and does not depend on a specific domain.

    Keywords: threat analysis, knowledge base, information security, MITRE ATT&CK, standardization

  • Comparison of Agile BPM-Based CRM Development with Anti-Pattern Hard Coding

    Software development, namely CRM-systems to improve the efficiency of the company, regardless of the area, is the most effective for business in terms of organizational and managerial activities. An important aspect of the successful implementation and implementation of the system in the company is the principle of developing and building the system architecture at the server level. For users to work in the system, a deep analysis of the company's business processes and the projection of technical requirements, both on the user interface and on the system's performance, are required. The correctness of the system is based on an important factor - further support of the existing code, this requirement is relevant for any project and depends on the initially chosen method of system development and the quality of tasks performed by programmers.

    Keywords: CRM-system, BPM, hardcode, development, flexible settings

  • Decentralized data Registry in Sovereign Identity Technology

    This article discusses the practical implementation of the self sovereign system based on the technology of a distributed decentralized data registry, also known as blockchain. An implementation of the system based on the Proof of Stake (PoS) consensus-building mechanism is presented, which provides a number of advantages over alternative implementations described in the literature. The results of measuring system performance in comparison with known implementations based on Proof of Work (PoW) are presented, confirming the high efficiency of the proposed solution.

    Keywords: decentralized, user-centric, identity-based encryption, blockchain, self Sovereign identity system

  • Application of ontologies in learning systems

    The article provides general information about ontologies (including definitions of ontology), its formal (mathematical) model, and also provides a step-by-step process for developing an ontology. The areas of application of ontologies are considered and special attention is paid to the use of ontologies in the field of education. There are some suggestions about using ontologies as a knowledge base for an information security learning system. Also the fragment of a graphical representation of an ontology for biometrics, which is one of the areas of information security, is given. Ontology for biometrics is based on the national standard and developed in the Protege system.

    Keywords: biometrics, knowledge, information security, knowledge representation model, learning system, learning, ontology, ontological model, OWL, RDF

  • 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

  • Personnel management in a real estate agency

    The dynamic model of personnel management in a real estate agency is investigated. The structure of the management system includes a real estate company as a Leader and a realtor as a Slave. The relations between them are built on the basis of a hierarchy corresponding to the information regulations of the Stackelberg games. Motivation is used as a method of hierarchical management. Algorithms for achieving equilibrium in different information regulations are presented. The numerical implementation of these algorithms is based on simulation modeling, the results are analyzed.

    Keywords: real estate company, hierarchy, simulation, stackelberg's game, stackelberg's game with feedback, motivation, leader, slave, dynamic system

  • Analysis of identification methods when determining the contours of skins from photographs

    The article discusses correlation methods of image identification. An algorithm of the "rare grid" method has been developed.

    Keywords: image identification, algorithm, recognition, cutting, reference frame, element correlations, minimum search