INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES

The use of the Isolation Forest model for anomaly detection in measurement data

Valeriy Aschepkov — Tue, 02 Apr 2024 00:00:00 +0300

The subject of the research is the Isolation Forest model, which is a powerful and efficient tool for detecting anomalies in measurement data and outliers, applicable in various fields where ensuring high accuracy and reliability of measurements is important. The goal of the study is to apply the Isolation Forest model to identify unusual or anomalous patterns that differ from typical patterns in the output data. This is achieved by isolating anomalous patterns from normal ones through the construction of multiple different decision trees. The task of the research is to detect outliers in data obtained during the preparation for international comparisons on the state primary standard for mass and volume flow rate of fluid, mass and volume of fluid flowing through a pipeline, by measuring with a сoriolis flowmeter. Data collected during metrological studies undergo processing by the model to detect anomalies. This model analyzes the data and identifies anomalous or outlier values that may indicate systematic or random measurement errors. It enables quick and efficient detection of even the smallest deviations in the data, helping to maintain high accuracy and reliability of measurement results. The main methods for detecting outliers in statistical analysis, which are distribution-independent, are the Grubbs' criterion, interquartile range distribution, and standard deviation. They are sensitive to sample size but are simple and understandable tools. However, the Isolation Forest model also has its limitations, particularly it can be resource-demanding for large datasets. Additionally, it is necessary to consider that using the model requires proper parameter tuning to achieve optimal results. The results of the research include assessment of the Isolation Forest model's effectiveness by comparing it with traditional outlier detection methods. Comparative analysis of the results of different approaches to the same task is an effective method for evaluating the model's performance. Conclusion. The article concludes with the perspective of further research development in this direction. The work will focus on further developing methods for detecting anomalies in measurement data and improving the accuracy and reliability of measurement results in various application fields, which can find broad applications in science and industry.

Study of adsorption of household gas molecules on electrophysical properties of porous silicon

Maksym Kogdas — Tue, 02 Apr 2024 00:00:00 +0300

Purpose. This research comprehensively investigates the adsorption of household gas molecules on porous silicon surfaces and its impact on the electrophysical properties of the material. The primary aim is to understand how the adsorption process influences the electrical conductivity and capacitance of porous silicon. Methodology. The study employs various electrophysical analysis methods to measure changes in the material's conductivity and capacitance caused by gas adsorption. Furthermore, the research explores optimal conditions for detecting household gas and establishes the correlation between the degree of adsorption and alterations in electrophysical parameters. Originality. The research contributes novelty by not only revealing increased conductivity due to adsorption but also significant changes in capacitance, providing a foundation for developing efficient gas sensors. Additionally, the article discusses the potential applications of porous silicon in developing novel materials for gas sensors to detect various airborne pollutants. Results. In addition to the previously mentioned findings, the article highlights the results of experiments studying the influence of different concentrations of household gas on the electrophysical characteristics of porous silicon. This insight refines optimal parameters for the effective detection of gas pollutants. The research also discusses the applicability of the results in producing environmentally friendly and highly efficient sensor systems. Practical Value. The obtained conclusions deepen our understanding of the interaction between porous silicon and household gas, crucial for advancing gas sensor technologies. The study opens broad possibilities for applying porous silicon in highly sensitive and reliable gas sensors for diverse practical applications, including safety monitoring and air quality control in industrial and domestic settings. The practical implications extend to the development of real-time, eco-friendly sensor systems.

A modified method of self-recovery of distributed software in heterogeneous computer systems

Maksym Volk, Maksym Hora — Sat, 30 Mar 2024 00:00:00 +0200

The object of research is the distributed computing process in heterogeneous computer systems. The subject of the research is methods of self-healing for distributed software on heterogeneous computer systems. The goal is to increase the efficiency of distributed data processing systems with support for the functional stability of the computing process by developing a modified method of self-healing of distributed software. Tasks: to investigate the existing methods of restoring the distributed computing process, to draw conclusions about their advantages and disadvantages; on the basis of mathematical models of tasks, computing resources and existing methods of resource allocation, develop a modification of the method of self-recovery of distributed software taking into account management strategies, finding the best solution for the selected criteria, reducing energy consumption during the execution of tasks; conduct a number of experiments comparing the developed method with existing ones. Research methods are based on the use of set theory, general systems theory, and simulation modeling theory. The results of the experiments obtained during the simulation of the allocation of software tasks to computing resources in a simulated simulation environment and the simulation of the computing process during self-recovery in case of resource failures confirm the effectiveness of the proposed method. Conclusion: the application of the method in distributed computing control systems does not increase the time the system spends on performing the task in the absence of failures, at the same time, in the presence of failures, it allows to restore the functionality of the software task faster and reduces the execution time by 8–17%, and energy consumption by 7–12%. There is also an increase in efficiency with an increase in the size of the tasks and the probability of failures. The development of technologies for automated or automatic use of methods of resource allocation and self-recovery can be indicated as areas for future research.

Analysis of communities and groups in social networks as a significant factor of influence on cryptocurrency rates

Olena Gavrilenko, Mykhailo Myagkyi — Sat, 30 Mar 2024 00:00:00 +0200

Currently, most existing cryptocurrency exchanges do not have tools in their arsenal that would allow them to verify and investigate information disseminated on social media regarding a particular cryptocurrency. This allows to conduct research with the subsequent development of an appropriate tool that, if used correctly, will provide users with recommendations on how to proceed with the cryptocurrency under investigation. Based on this advice, interested parties will be able to adjust their decisions regarding further financial steps. As part of this task, it is important to choose a social network that would best meet the requirements, as this is what determines the impact of celebrity publications on the formation of prices for a particular cryptocurrency at a certain point in time. The importance and existence of this influence has been previously proven by statistical methods. The purpose of the study is to identify and analyse the key aspects when choosing social networks for further monitoring of social groups in order to analyse the impact of posts on the course of the chosen cryptocurrency. The object of the study is social networks. A set of selection criteria, coefficients of their importance, and statistical data on the selected social networks were used as input data, on the basis of which the values of the alternatives (social networks) will be obtained. The objective of the study is to evaluate and rank social networks in order to choose the one that will best meet the specifics of analysing the impact of social media posts on the cryptocurrency rate. Research methods. The ranking of social networks was carried out by the value of the value function of alternatives, calculated using the linear convolution method. Results. As a result of the research, an algorithm has been developed that allows analysing the selected social networks for their compliance with the formulated criteria. The results of the experiment with the selected social networks were presented. As a result, a ranked list of them is obtained. Based on the results obtained, the authors will develop an information technology for determining the impact of posts of famous people in social networks on cryptocurrency rates.

Definition of the requirements architecture for IT solution as a business analytics product

Denis Gobov, Natalia Shevchenko — Tue, 02 Apr 2024 00:00:00 +0300

The subject of research in the article is approaches to understanding and interpreting the concept of the architecture of requirements for an IT solution. The purpose of the work is to define the architecture of software requirements for a better understanding and further implementation of this concept in the practice of software development. The article addresses the following tasks: analyze approaches to the classification of requirements to determine common and distinctive characteristics and their impact on the definition of the architecture of requirements; examine requirements engineering standards to find the definition and any relationship to the requirements architecture; consider approaches to building a set of requirements and using templates to describe them to identify optimal strategies for business analytical processes and their impact on the architecture of requirements. The following methods are used: comparative analysis, including comparison and generalization of different classifications of requirements taking into account their impact on the definition of requirements architecture, review of literature and standards related to requirements engineering, as well as analysis of their impact on the process of formation of requirements architecture, analysis of documentation with the aim identifying optimal strategies for building the requirements architecture, as well as analyzing the use of templates for describing requirements and their importance in defining the requirements architecture. In addition, the requirements quality criteria analysis results were interpolated to identify relationships between the quality of requirements and their architecture, which made it possible to determine the optimal approaches to building the architecture of requirements that meet the requirements of software quality. The following results were obtained: approaches to understanding requirements in software development were investigated, generally accepted classifications of requirements and characteristics of quality requirements were given, and links of the chain "requirements – quality of requirements – approaches to description of requirements – standards – architecture of requirements" were analyzed with further logical interpolation of the studied context on the architecture of requirements, the author's definition of the concept of architecture of requirements is proposed. Conclusions. Requirements architecture can be based on different architectural frameworks and depends on software development methodologies, but at the same time, it can vary depending on industry standards and the needs of a specific project. Also, requirements architecture can use certain document templates, but it is not limited to them.

Ontological description method for building service-oriented distributed learning systems

Zoia Dudar, Svitlana Litvin — Sat, 30 Mar 2024 00:00:00 +0200

The subject of the research is the analysis and justification of the use of software engineering processes based on ontologies of data access and representation of access to knowledge bases and knowledge reuse in the language of algebra of finite predicates, which is a class of descriptive logics. This approach allows you to use the advantages of ontologies and logic programming in the refactoring of distributed distance learning systems. The purpose of the work is to create a formalism for describing the interaction of services and algorithms for building web service interfaces for the implementation of an effective SOA system using the paradigm of access to data based on ontologies. To achieve the goal, the following tasks were solved: an analysis of the main types of interaction structures of SOA services, an overview of implementations of systems working with a family of descriptive logic languages, namely, algebra of finite predicates, and a description of the structure of the ontology necessary for the operation of service-oriented systems, which has the markup of the Semantic Web standard using finite predicate algebra equations. The task is an urgent task of ensuring the organization of interaction of Internet resources in the development of distributed virtual learning systems, and such interaction is enabled by the service-oriented architecture of software development. The article examines modern technologies of the Semantic Web and their role in ensuring the creation of applied software systems of distributed learning resources built using distributed interactive services. The considered methods and materials include methods of algebra of finite predicates, theory of algorithms, object-oriented design, theory of unification. The results. The semantics of the SOA system is obtained, which makes it possible to describe SOA systems in the languages of descriptive logic. The effectiveness of the mathematical formalism of the algebra of finite predicates for the tasks of logical analysis of applied ontologies, the use of knowledge reuse methods, and the description of service-oriented systems is shown. The necessity of using algorithms for automatic construction of web interfaces is shown. The conclusions of the work highlight the advantages of the researched solution, namely, algorithms for the automated construction of web service interfaces for SOA architecture, which make it possible to automatically build web service interfaces. Algorithms differ in a more general model and speed of work and require an assessment of complexity.

Architecture and iot security systems based on fog computing

Oleh Zhurylo, Oleksii Liashenko — Sat, 30 Mar 2024 00:00:00 +0200

The subject of the study is is the security architecture of the Internet of Things (IoT) based on fog computing, which allows providing efficient and secure services for many IoT users. The goal is to investigate the security architecture for IoT systems based on fog computing. To achieve the goal, the following tasks were solved: the concept of fog computing is proposed, its architecture is considered and a comparative analysis of fog and cloud computing architectures is made; the principles of designing and implementing the architecture of a fog computing system are outlined; multi-level security measures based on fog computing are investigated; and the areas of use of fog computing-based Internet of Things networks are described. When performing the tasks, such research methods were used as: theoretical analysis of literature sources; analysis of the principles of designing and implementing the security architecture of the Internet of Things; analysis of security measures at different levels of the architecture. The following results were obtained: the architecture of fog computing is considered and compared with the cloud architecture; the principles of designing and implementing the architecture of fog computing systems are formulated; multi-level IoT security measures based on fog computing are proposed. Conclusions: research on IoT security systems based on fog computing has important theoretical implications. The fog computing architecture, in contrast to the cloud architecture, better meets the demand for high traffic and low latency of mobile applications, providing more advantages for systems that require real-time information processing. When designing and implementing the architecture of fog computing systems, the factors of memory capacity, latency, and utility should be taken into account to effectively integrate fog technologies with IoT. To ensure a high level of system security, multi-level security measures should be implemented using both software and hardware solutions.

Enhancing the security of web applications through innovative patterns of integration of artificial intelligence

Iryna Zamrii, Ivan Shakhmatov — Sun, 31 Mar 2024 00:00:00 +0200

Ensuring the security of digital operations, especially in the areas of e-commerce and financial transactions, remains increasingly relevant. Therefore, the subject of research is the development of a specialized software library. This library aims to improve the security of web applications. The purpose of this study is to develop a software library that uses artificial intelligence and machine learning methods to analyze and improve the level of security of financial transactions. The use of these advanced technologies helps automate the detection of potentially fraudulent or risky transactions, thereby providing a higher level of user protection. The following tasks are solved in the article: analysis of modern methods of processing financial transactions and identification of possible security threats; development of a UML diagram of library classes for processing and analyzing financial transactions; testing and validation of the developed artificial intelligence model for assessing the security of financial transactions on real financial data. Machine learning methods were defined and applied using the scikit-learn library in Python, the algorithms of which are capable of analyzing large volumes of data and identifying potential risks with high accuracy. This ensures effective integration of artificial intelligence technologies. The following results were obtained in the work: the criteria for assessing the riskiness of financial transactions for the identification of potential risks are defined; the program operation algorithm is described, which includes procedures for determining and classifying transaction risks; pseudocode is presented, which illustrates the structure of classes and methods of the model, opening opportunities for its adaptation and scaling; methods of generating test data reproducing realistic scenarios of financial transactions have been developed; an analysis of the results was carried out to assess the effectiveness of the developed model. In conclusion, the results of research and testing allow us to evaluate the model's response to various data and its effectiveness in real conditions, as the work presents examples of processing various types of transactions. In addition, the study presents not only the development and validation of the developed model, but also the prospects of its use on a larger scale, integration with existing web applications.

The method of linear-logical operators and logical equations in information extraction tasks

Andrii Kozyriev, Ihor Shubin — Sat, 30 Mar 2024 00:00:00 +0200

Relational and logical methods of knowledge representation play a key role in creating a mathematical basis for information systems. Predicate algebra and predicate operators are among the most effective tools for describing information in detail. These tools make it easy to formulate formalized information, create database queries, and simulate human activity. In the context of the new need for reliable and efficient data selection, a problem arises in deeper analysis. Subject of the study is the theory of quantum linear equations based on the algebra of linear predicate operations, the formal apparatus of linear logic operators and methods for solving logical equations in information extraction tasks. Aim of the study is a developing of a method for using linear logic operators and logical equations to extract information. This approach can significantly optimize the process of extracting the necessary information, even in huge databases. Main tasks: analysis of existing approaches to information extraction; consideration of the theory of linear logic operators; study of methods for reducing logic to an algebraic form; analysis of logical spaces and the algebra of finite predicate actions and the theory of linear logic operators. The research methods involve a systematic analysis of the mathematical structure of the algebra of finite predicates and predicate functions to identify the key elements that affect the query formation process. The method of using linear logic operators and logical equations for information extraction is proposed. The results of the study showed that the method of using linear logic operators and logical equations is a universal and adaptive tool for working with algebraic data structures. It can be applied in a wide range of information extraction tasks and prove its value as one of the possible methods of information processing. Conclusion. The paper investigates formal methods of intelligent systems, in particular, ways of representing knowledge in accordance with the peculiarities of the field of application and the language that allows encoding this knowledge for storage in computer memory. The proposed method can be implemented in the development of language interfaces for automated information access systems, in search engine algorithms, for logical analysis of information in databases and expert systems, as well as in performing tasks related to object recognition and classification.

Fuzzy logic in the problems of determining the economic parameters of project implementation

Olha Matviienko, Serhii Zakutnii — Sat, 30 Mar 2024 00:00:00 +0200

The goal of this work is to forecast project execution terms and its main economic parameters using graph theory and fuzzy logic methods. The subject of research in the article is the method of calculating the main properties or parameters of the project, forecasting the terms of its implementation and the possibility of taking into account force majeure situations. The article discusses the task of finding the optimal plan for the project of creating an e-commerce site and calculating its main economic parameters. The work uses methods of the theory of network planning and management. Fuzzy logic methods are used to solve the fuzzy optimization problem. Graph theory methods, namely the CPM critical path method, are used to forecast project deadlines. The following results were obtained: the main economic parameters were calculated for two versions of the project to create an e-commerce site – sequential, when the team does not have many developers to implement it (or enough resources), and parallel execution of work, which allows you to optimize the execution time by involving additional workers. The cost of both projects was also calculated, which in the future can help managers draw conclusions regarding the implementation of one or another planning option for this type of project. For the first project, the project work plan will be completed in a time not exceeding 230 days, with a reliability of 30%. Or does not exceed 295 days with a reliability of 80% percent. For the second project, the project work plan will be completed in a time not exceeding 230 days, with a reliability of 30%. Or does not exceed 278 days with a reliability of 70% percent. Conclusions: the paper proposes a fuzzy mathematical model for finding the optimal plan and calculating the main economic parameters of the project of creating an e-commerce site with a fuzzy set of plans and a vaguely defined goal. The work also presents a method for solving this problem. The obtained results of the research are of great value for planning the project, for solving the question of the feasibility of its initiation, for forecasting the resources that will be needed for its implementation. These indicators are essential for improving processes and correct allocation of work, which can help strengthen competitiveness and increase project profits.

Analysis of passenger transportation and the public transportation impact on the reduction in a smart city

Yurii Matseliukh, Vasyl Lytvyn — Sat, 30 Mar 2024 00:00:00 +0200

The state of atmospheric pollution is determined by the growth of the population, the amount of transport and the generated volumes of emissions. The object is the process of analyzing passenger transportation in the city. The subject is passenger transport analysis methods. Purpose: analysis of passenger transportation and approaches to optimization of public transport based on the concept of a smart city. Tasks: analysis of passenger transportation, classification of existing conceptual approaches to optimization of public transport with low carbon emissions, systematization of existing methods, means and types of neural networks in smart cities, analysis of successful implementation projects. Methods of statistical analysis, linear and non-linear interpolation, logical generalization, comparison, grouping, analysis and synthesis. Results: the analysis of passenger transportation in the city revealed that statistical data sets indicate a decrease in the main indicators of passenger traffic and an increase in the volume of emissions of carbon-containing compounds. The classification of existing approaches to the optimization of public transport is carried out according to the priority of public transport, hybridization and electrification of vehicles and the implementation of IT monitoring. During the systematization of methods and means in smart cities, the following are highlighted: smart transport systems; electric vehicles; transport sharing networks; smart applications and information systems; innovative payment systems; unmanned vehicles; information boards and announcement systems; networks of bicycle paths and equipped sidewalks; environmental monitoring systems. Among neural networks, recurrent, convolutional, and deep neural networks have been proposed as those that contribute to route optimization and traffic prediction. Conclusions: the statistical analysis of passenger transportation established that reducing carbon dioxide emissions is an unresolved task for both public transport and the transportation system. It is proposed to include methods and means that optimize public transport, reducing the carbon footprint of the initiatives of implementing the concept of a smart city, which are successful all over the world. It is proposed to use recurrent, convolutional and deep neural networks to optimize passenger transportation in smart cities.

A method to enhance Apache Spark performance based on data segmentation and configuration parameters settings

Serhii Minukhin, Nikita Koptilov — Sat, 30 Mar 2024 00:00:00 +0200

When using modern big data processing tools, there is a problem of increasing the productivity of using modern frameworks in the context of effective setting of various configuration parameters. The object of the research is computational processes of processing big data with the use of technologies of high-performance frameworks. The subject is methods and approaches to the effective setting of configuration parameters of frameworks in the conditions of limitations of virtualization environments and local resources. The purpose of the study is to improve the performance of Apache Spark and Apache Hadoop deployment modes based on a combined approach that includes preprocess segmentation of input data and setting of basic and additional configuration parameters that take into account the limitations of the virtual environment and local resources. Achieving the set goal involves the following tasks: create a synthesized set of WordCount test data for using input data segmentation methods. Determine the composition of general and specific Apache Spark and Apache Hadoop configuration parameters that most affect the performance of frameworks in Spark Standalone and Hadoop Yarn (FIFO) deployment modes. Justify changes in the values of the configuration parameters (accepted by default) by setting the level of parallelism, the number of partitions of the input file according to the number of processor cores, the number of tasks assigned to each core and the system executor. Conduct experimental research to substantiate theoretical results and prove their use in practice. Methods. The research used the following methods: statistical analysis; a method of generating test data based on defined segmentation characteristics with arbitrary volumes of data; a systematic approach for comprehensive evaluation and analysis of performance of frameworks based on selected configuration parameters. The results. On the basis of the developed system of parameters for evaluating the performance of the studied frameworks, experiments were carried out, which include: the application of the method of segmentation of input data based on the division of the input file into paragraphs (lines) for different values of the ranges of the number of words and the number of letters in each word; setting the main parameters and specific ones, in particular, partitioning and parallelism, taking into account the characteristics of the virtual environment and the local resource. According to the obtained results, a detailed analysis of the use of the proposed methods to improve the performance of the studied frameworks with recommendations for choosing the optimal values of data segmentation parameters and configuration parameters was carried out. You are snowmen. The obtained results of the experiments allow us to conclude that the use of the proposed methods of setting the configuration parameters of Spark and Hadoop will increase the processing productivity: for small files (0.5–1 GB) on average up to 25–30%, for large ones (1.5–2.5 GB ) – up to 10–20% on average. At the same time, the average value of the execution time of one task decreased by 10-15% for files of different sizes and with different number of words in a line.

Semantic clustering method using integration of advanced LDA algorithm and BERT algorithm

Volodymyr Narozhnyi, Vyacheslav Kharchenko — Sat, 30 Mar 2024 00:00:00 +0200

The subject of the study is an in-depth semantic data analysis based on the modification of the Latent Dirichlet Allocation (LDA) methodology and its integration with the bidirectional encoding representation of transformers (BERT). Relevance. Latent Dirichlet Allocation (LDA) is a fundamental topic modeling technique that is widely used in a variety of text analysis applications. Although its usefulness is widely recognized, traditional LDA models often face limitations, such as a rigid distribution of topics and inadequate representation of semantic nuances inherent in natural language. The purpose and main idea of the study is to improve the adequacy and accuracy of semantic analysis by improving the basic LDA mechanism that integrates adaptive Dirichlet priorities and exploits the deep semantic capabilities of BERT embeddings. Research methods: 1) selection of textual datasets; 2) data preprocessing steps; 3) improvement of the LDA algorithm; 4) integration with BERT Embeddings; 5) comparative analysis. Research objectives: 1) theoretical substantiation of LDA modification; 2) implementation of integration with BERT; 3) evaluation of the method efficiency; 4) comparative analysis; 5) development of an architectural solution. The results of the research are that, first of all, the theoretical foundations of both the standard and modified LDA models are outlined, and their extended formula is presented in detail. Through a series of experiments on text datasets characterized by different emotional states, we emphasize the key advantages of the proposed approach. Based on a comparative analysis of such indicators as intra- and inter-cluster distances and silhouette coefficient, we prove the increased coherence, interpretability, and adaptability of the modified LDA model. An architectural solution for implementing the method is proposed. Conclusions. The empirical results indicate a significant improvement in the detection of subtle complexities and thematic structures in textual data, which is a step in the evolutionary development of thematic modeling methodologies. In addition, the results of the research not only open up the possibility of applying LDA to more complex linguistic scenarios, but also outline ways to further improve them for unsupervised text analysis.

The “load balancing” and “adaptive task completion” algorithms implementation on a pharmaceutical sorting conveyor line

Igor Nevliudov, Vladyslav Yevsieiev, Svitlana Maksymova, Oleksandr Klymenko — Tue, 02 Apr 2024 00:00:00 +0300

The subject matter of the article is advantages and disadvantages of using the "load balancing" and "adaptive task execution" algorithms on the pharmaceutical sorting conveyor. The goal of the work is to analyze the Load Balancing (LB) and Adaptive Task Completion (ATC) sorting algorithms application on pharmaceutical sorting conveyor lines. And also, to consider their advantages and disadvantages in the context of optimizing sorting processes for pharmaceutical products. The following tasks were solved in the article: analysis of the latest research and publications on the research topic; study of the specifics of the application of algorithms for sorting pharmaceutical products on conveyor lines to balance the load on sorting robots; analysis of the Load Balancing (LB) algorithm from the point of view of its application for load balancing on conveyor lines with sorting robots in the field of pharmaceuticals; development of the Load Balancing algorithm for load balancing on conveyor lines with sorting robots in the pharmaceutical field; analysis of the Adaptive Task Completion (ATC) algorithm from the point of view of its application for load balancing on conveyor lines with sorting robots in the field of pharmaceuticals; development of a general Adaptive Task Completion (ATC) algorithm for load balancing on conveyor lines with sorting robots in the pharmaceutical field; highlighting the advantages and disadvantages of the specified algorithms. The following methods were used: simulation modeling methods. The following results were obtained – the advantages and disadvantages of Load Balancing and Adaptive Task Completion algorithms for load balancing on conveyor lines with sorting robots in the pharmaceutical field are formulated; recommendations are given, in which situations, under which conditions, which algorithm should be used. Conclusions. In the context of the pharmaceutical industry, where not only speed but also sorting accuracy is important, Adaptive Task Completion may be a better choice because it takes into account different criteria and dynamically responds to changing conditions. On the other hand, Load Balancing can be effective in environments where sorting speed is paramount, and tasks are homogeneous.

Analysis and justification of the use of existing blockchain solutions for the protection of digital assets

Glib Tereshchenko, Iryna Kyrychenko — Tue, 02 Apr 2024 00:00:00 +0300

The subject of this article is consideration of modern blockchain solutions and their potential use in the context of digital asset protection. Various aspects of blockchain technology are explored, including consensus mechanisms, security levels, and functionality. The goal of the work is a systematic analysis and justification of the application of various blockchain solutions for the protection of digital assets. The article is aimed at determining the effectiveness and feasibility of using specific blockchain protocols and their functional elements to ensure the safety, reliability, and integrity of digital assets. The following tasks were solved in the article: consideration of modern blockchain technologies and consideration of their role in ensuring the security of digital assets. Conducting a detailed analysis of popular blockchain protocols, including Bitcoin, Ethereum, and Hyperledger Fabric, with a focus on their security against various types of cyber threats and attacks. The following methods are used: analysis of blockchain protocols, expert evaluations of the effectiveness of protection of digital assets, and study of the technical features of each solution. The following results were obtained: clearly defined advantages and disadvantages of each protocol were obtained, taking into account their applicability in the field of digital assets in various fields of application, such as semantic analysis of texts, E-Learning, Big Data, DDP-systems, finance, etc. In addition, the issue of network privacy in the context of information protection was investigated and justifies the choice of the optimal blockchain solution for a specific use. Conclusions: The article provides readers with an overview of how to effectively use blockchain to ensure the reliability and security of digital assets in a variety of usage scenarios. In today's digital world, where the value of digital assets is growing exponentially, protecting them from cyber threats becomes a critical task. Blockchain technologies, originally developed for cryptocurrencies, have gained recognition as an effective tool in the field of cyber security. The importance of standardization and regulation in the field of blockchain technologies to ensure their effective integration and compliance with the requirements of the law is put forward.

Ontological model of structure and parameters of components in high-tech product modernization projects

Oleg Fedorovych, Leonid Malieiev — Tue, 02 Apr 2024 00:00:00 +0300

The subject of the article is models representing the structure and parameters of components in high-tech products based on the analysis of technical documentation in modernization projects. The purpose of the proposed research is to enhance the quality of modernization processes of high-tech products by forming an ontological model of the product with innovative components, considering the diversity of information support. The article addresses the following tasks: studying the main methods and technologies of system representation of complex product structure; forming a model of structural-functional decomposition of a high-tech product, creating an ontological model of the structure and parameters of a high-tech product based on technical documentation. The following methods are applied: systemic approach, methods of functional-structural decomposition, set theory, ontology construction methods, semantic models. The following results were obtained: The main methods of system representation of complex product structure were investigated, based on the following principles: decomposition of complex product architecture, layering of complex product representation, multivariate synthesis of component architecture. The main directions and advantages of using 3D technologies for solving design tasks in modernization projects of high-tech product components are considered. The decomposition of a high-tech product into component parts and partial parameters is proposed, taking into account functional, structural, and parametric characteristics. An ontological model of the structure and parameters of a high-tech product is formed based on a set of technical documentation and considering additional heterogeneous sources of information. Innovative elements are identified, the description of which may be fuzzy. Conclusions. The proposed ontological model can serve as a basis for finding similar solutions regarding the design of innovative components in the precedent database, which is properly structured. In the absence of similar design solutions, innovative component design can be carried out using 3D technologies based on supplementing fuzzy information in the semantic model.

Automated design of embedded digital signal processing systems on SOC platform

Tue, 02 Apr 2024 00:00:00 +0300

The object of the study is the procedures for automated design and analysis of digital signal processing algorithms on the SoC technology platform. The subject of the study is models, methods and procedures for designing and optimal selection of SoC components for the implementation of digital signal processing algorithms for audio spectrum. The aim of the study is to develop models and procedures for determining the possibilities of a compromise distribution of signal processing algorithm computations in the cycle of computer-aided design on the SoC technology platform in terms of performance and the feasibility of using hardware and software algorithms realization. The article solves the following tasks: consideration of the procedures for interacting the processor core with programmable logic as part of system-on-chip systems; development of procedures for computer-aided design and analysis of signal processing systems using programming languages and hardware description languages for the implementation of embedded systems. The following methods are being used: implementation of digital signal processing algorithms in the C programming language and high-level synthesis tools for realizing IP blocks, diagnostic experiment by generating test signal patterns, and analysis of the processing results at the system output. The results achieved. Based on the analysis of the procedures for the interaction of the processor core and programmable logic on the selected SoC platform, a model of the audio spectrum signal processing system is designed. The practical implementation was performed based on the Vivado/Vitis/Vitis HLS CAD tool stack. The proposed model was verified using a programmable test signal generator and analyzing the obtained characteristics of digital filters at the system output. Conclusions. The article analyzes the principles of designing embedded information processing systems implemented in system-on-chip. The principles of building and analyzing digital signal processing systems based on system-on-chip containing programmable logic and processor parts are considered. The developed methods have been tested on the algorithms of CIC and FIR filters on the technological platform of SoC FPGA of the ZYNQ-7000 family of Xilinx company.

Models of digitalization of hr management systems in security-oriented organizations

Khrystyna Matkivska, Oleh Zachko — Tue, 02 Apr 2024 00:00:00 +0300

The subject matter of the article is the study of operational processes of digitalization of HR-management of security-oriented systems in the current changing situation of our country. The goal of the work is to study the indicators of effective communication between employees and determine the number of potential communication channels, as well as to study automated communication between the personnel of security-oriented systems. The following tasks: formation of a centralized model for managing the operational processes of HR management of security-oriented systems, unlocking the potential of personnel in the digitalization of personnel processes of security-oriented systems. The methods are used: methods for implementing the continuous development of security-oriented systems, a centralized model for managing the operational processes of HR management of civil protection and an end-to-end process of automated HR communication within government agencies are developed and presented. The following results: determination of the number of potential communication channels, a graph of the number of stakeholders, a picture of the end-to-end process of automated HR communication within government agencies, a centralized model for managing HR operational processes of security-oriented systems, and the potential of personnel in the digitalization of HR processes. Conclusions: the driving forces behind the digital transformation of government agencies include meeting the expectations of the staff, digital transformation of the HR industry, and digital innovations in the civil service. Areas of digital transformation of HR management in security-oriented systems include a digital workplace (online employee profile), digital HR processes of the organization, digital services and online self-service of personnel. Among them, the digital HR process mainly focuses on training and development, open and effective communication within the civil service, and personnel evaluation functions. The digital transformation will lead to certain consequences, such as parallelization and transition between the old and new HR management systems, and will affect the productivity and digital ethics of the state.

Determination of the minimum number of periods for assessing the sustainable development indices of the EU countries using the methods of ordinal statistics

Sat, 30 Mar 2024 00:00:00 +0200

The subject matter of the article is the process of assessing the sustainable development indices of the European Union countries. The goal of the article is to develop a methodology for determining the number of periods for which it is necessary and sufficient to assess the sustainable development indices of states. The article results the following task: to develop a methodology for determining the law of distribution of random variables of sustainable development indices. Determination of the minimum number of periods for assessing the sustainable development indices of the European Union countries. Methods used: parametric and ordinal statistics. The following results are obtained: parametric and non-parametric methods of statistics, their advantages and disadvantages are considered. Various methods of estimating the distribution function for small samples, in particular the method of rectangular contributions and the method of uncertainty reduction are analysed. Particular attention is paid to the problem of changing the law of scattering of quality indicators when changing the conditions of technology. A graph-analytical method for identifying the law of distribution of random variables based on a small amount of statistical information is proposed. For this purpose, the theory of ordinal statistics was used. A step-by-step methodology for identifying the law of distribution of random variables using 10 ordered values has been developed. The mathematical expectations of ordinal statistics for three distribution laws are proposed. A methodology for determining the number of periods for assessing the indices of sustainable development of countries using ordinal statistics is developed. The study is based on the analysis of statistical data for the last ten years and their ordering in ascending order. The mathematical expectations of ordinal statistics are used to select appropriate distribution laws. Given the limited information available when working with small samples, the article proposes a methodology that allows obtaining the maximum amount of information from the available data. The developed approach makes it possible to take into account the uncertainty of the phenomenon under study and make informed decisions based on statistical analysis. Conclusions: based on the knowledge of the law of distribution, a methodology for determining the minimum number of periods for assessing the sustainable development indices of the European Union countries is proposed. Testing of the methodology on real numerical data has confirmed that the minimum number of periods is seven, provided that the distribution law follows the normal law.

Assessment of the quality of the labour safety management system in accordance with the requirements of the international standard ISO 45001:2018 at the stage of operation

Tue, 02 Apr 2024 00:00:00 +0300

The subject matter of the article is the assessment of the quality of the occupational safety management system. The goal of the article is to develop a methodology for assessment of the occupational safety management system at the stage of operation. The article solves the following task: to investigate the possibility of applying methods for analysing the dynamic characteristics of the occupational safety management system and to develop algorithms and methods for using the criteria of non-parametric statistics. Methods are used: qualimetry and mathematical statistics. The following results were obtained: an analysis of the requirements of the international standard ISO 45001:2018 was carried out to determine the need to monitor, measure and analyse the functioning of the occupational safety management system, which revealed that the effectiveness of the development and implementation of the occupational safety management system depends on the assessment methodology. An analysis of existing research and publications on the evaluation of processes, including those related to occupational safety, is carried out. The methods for evaluating mathematical systems for processing and controlling gross errors and stationarity, which are key to the analysis of occupational safety management processes, are considered. Non-parametric criteria for checking the stationarity of random processes are considered in detail. Sequences of means and means squares are compared with expected values to determine whether rejections of the stationary hypothesis are justified. The expediency of using these methods for analysing occupational safety management systems is determined. The dynamic nature of the processes and the importance of monitoring and data analysis to ensure effective safety management practices are analysed. Conclusions: The application of methods for analysing the dynamic characteristics of the occupational safety management system is substantiated and algorithms and methods for using the criteria of non-parametric statistics are developed, which allow to obtain an assessment of the system, taking into account the limited information about its indicators and the lack of knowledge of the law of their distribution as a random variable.