Information Technology for Education, Science, and Technics

The study focuses on the creation of an organizational mechanism tailored towards monitoring and regulating the transportation of hazardous materials, with a primary aim of enhancing safety protocols and ensuring compliance with environmental standards. By centring on the assessment of external environmental volatility, particularly within the context of a hybrid warfare scenario, the research endeavours to devise robust management strategies. The methodology adopted employs a multi-tiered evaluation system, meticulously scrutinizing distinct environmental variables to gauge instability levels. Leveraging entropy as a metric for gauging management efficacy, the study meticulously evaluates the facets of the management framework through hierarchical structures. The findings underscore the efficacy of the proposed organizational mechanism, meticulously crafted to cater to the unique requisites of the system and its stakeholders. The implementation of this mechanism is poised to streamline the transportation of hazardous materials, affording a more nuanced consideration of all pertinent aspects, thus fostering efficiency across the board.

The article focuses on comparing two visual attention analysis approaches based on a human focus group study and an artificial model of pre-attentive processing attention prediction. We substantiate eye-tracking as the suitable modality for visual attention studies through a literature review and bibliometric analysis. The study design is based on eye-tracking as the modality to test the hypothesis aimed to answer the research question. We explain the processes of the focus group formation and visual stimuli selection are explained, and perform a comparative analysis of the results yielded by both approaches is discussed. We suggest new perspective directions for pre-attentive processing phase studies regarding text recognition and mobile platforms’ peculiarities. We demonstrate that acquiring eye-tracking data from a focus group formed according to the target audience of visual representation tends to demonstrate similar or more effective results compare to the predictive model. The current study can be used as the starting point for visual representation creators, promoters, and users to form an understanding of visual attention analysis tools.

The article examines the importance of using geoinformation technologies for improving municipal management and urban development.A detailed analysis of the latest research and publications highlights the potential risks and challenges associated with the integration of advanced technologies. The paper proposes a combination of advanced tools and approaches for optimizing spatial data in the context of municipal management. The proposed technology emphasizes the benefits of a multi-threaded approach, potentially involving technologies such as NoSQL and PostGIS for efficient data management. Special attention is paid to the need to comply with the established standards of spatial database management. The proposal involves the use of a modern serveries architecture to optimize the processing and publication of data for web applications. The paper demonstrates the system design-using context and decomposition diagrams illustrating user interaction, administration, data storage, and output presentation functions. Model diagrams and business process notation (BPMN) are used to model the process of solving housing and utility problems.Because of modeling, a prototype of an interactive system specially designed for monitoring the urban infrastructure of Chernihiv has been developed. It implements solutions to key issues arising in the process of city development, ensures fast and efficient functioning of the municipal government, promotes better interaction with the community.The testing of the prototype shows the improvement of the efficiency of the city's housing and communal services.

The article analyzed how cross-disciplinary cooperation can ensure digital resilience. This cooperation should deliver toolsets for government, business, and citizens. Under consideration are telecoms, information and communication technology (ICT), internet infrastructure, and data centers. The subject is to find standards and best practices to amplify digital resilience. The system approach is the methodology using public domain sources, secondary data, and quantitative and qualitative observations. The author considers (i) specific key performance indicators (KPI) aligned with the EU Digital Compass and other regulations, (ii) environmental, social, and governance (ESG) practice, and (iii) business continuity metrics. Pertinent stakeholders can see holistic and in-depth data on their dashboards. The key findings demonstrate that cross-disciplinary cooperation is mandatory for a sustainable and resilient existence and has specific methods, metrics, and organizational forms. The central and regional government, businesses, and citizens can cover the digital resilience gaps based on transversal cross-disciplinary strategies, plans, and executions. It may have many organizational forms, particularly as a Platform. Such complex cooperation and toolsets allow stakeholders to reach digital resilience during poly-crises and disruption.

This study explores the development of a console application utilizing autonomous open-source Large Language Models (LLMs), specifically LLAMA 2, to automate the generation of paragraph highlights(outlines) for scientific articles. The research highlights a critical need to enhance the efficiency of processing and reviewing extensive literature, especially in fields overwhelmed with publications such as artificial intelligence. By automating the extraction of key highlights from paragraphs, the application aids researchers in swiftly identifying relevant studies without extensive manual review. Utilizing a qualitative research methodology, the project assesses various LLMs and integrates Whiteside’s method for optimal outlines generation. The findings suggest that the application effectively streamlines the review process, potentially transforming how academic literature is synthesized.

In most cases, the analysis of the autocorrelation systems bit error rate (BER) performance is often performed with random variables Gaussian approximation. While the use of Gaussian approximation simplifies analytical studies, it also results in a loss of the theoretical estimate accuracy. Our objective is to analyze the potential BER performance of a multichannel digital multiple access modem with noise signals of the white Gaussian noise type when operating over a channel with constant parameters in which an additive Gaussian noise acts. The BER performance analysis of a signal system is performed by applying the functional transformation of random components in the demodulator with the characteristic function apparatus use. This method relies on defining the overall density of the distribution by determining the distribution of one of the random variable’s terms. All terms have the same composition and represent the sum of mutually independent random variables. Having found the distribution of one of the terms, we can use its characteristic function to determine the characteristic of the total value distribution function. By applying the inverse Fourier transform, we acquire desired distribution density. The digital multichannel modem BER performance analysis determines the theoretical estimate of the system potential BER performance, which is necessary for the comparative analysis of systems with broadband signals. The study has shown that the application of this technique results in the acquisition of analytical expressions for calculating the potential BER performance of the modem, which is additionally confirmed by the results of simulation modeling.

The article deals with the problem of quality control of the tightness of the shell of nuclear reactor fuel elements. It is proposed to improve the control system by introducing an information and measuring module for detecting defects as a subsystem of the automated process control system of a nuclear power unit. The algorithm of the fractal method of quality control is presented, which determines the sequence of operations to determine the location, type and size of defects on the surface of the shells by calculating the fractal dimension indicators. A block diagram of the computing module for implementing the algorithm for estimating the fractal dimension of defects in the shell material was developed. The structural and functional scheme of the system was improved by integrating a computing module that provides data processing on the quality of the seal and the transfer of information to the control system. The practical value lies in the information and measuring unit for detecting defects, which allows real-time assessment of the quality of the shells’ tightness and transmitting data to an automated workstation for making decisions on the operation of leaky fuel elements.

This paper is dedicated to the problem of detecting anomalies in the particular time series data, which consists of wave-like data. Anomaly detection is implemented in various fields and can be used in many automated control systems. Wave-like data is characterized by such attribute as seasonality, and every data season is a wave that has a similar rise, top limit, and fall of data. In this case, detecting when the data have waves with different height and width is necessary. Setting only the usual limits by setting the minimum and maximum value on one axis and checking whether the data goes beyond the height limits is ineffective because, in this case, it does not take into account the data on the wavelength. Also, it is necessary to set different limits every time for different time series. Thus, it is necessary to develop an algorithm that can automatically separate waves, calculate the base characteristics of these waves, and, based on the conducted calculations, detect waves that do not correspond with the regular wave parameters. The solution to identifying anomalies in the particular type of time series data is a new method based on derivatives that can detect a rise, top limit, and fall of waves, split data by waves, and check the wave equivalence.

Aircraft maintenance (AM) is a set of operations at the operational stage to maintain airworthiness, the purpose of which is to prepare the aircraft for flights, maintain serviceability, etc. The analysis of possible failures and their consequences during maintenance is carried out “from top to bottom”. As a result of the decomposition, the presence of defects in functional subsystems is analysed. For the coordinated execution of operation processes, it is advisable to use simulation modelling. Therefore, the task of creating a simulation model of technical maintenance and repair of automatic transmission lines, which includes modules for diagnosis, fault finding, accumulation of diagnostic information for further processing, etc., is set and solved. The purpose of the study is to develop a model of multi-level component search for aircraft malfunctions during diagnostic processes. The subject of the research is the planning and management of operation as a stage of the life cycle of complex equipment. The following mathematical models and methods are used: system analysis, information theory, simulation modelling. A model of multi-level component fault finding during the diagnostics of the automatic transmission system is proposed, which will allow to optimize the duration and cost of maintenance of operational equipment.

The purpose of the research is to create a system for selecting table tennis equipment. Such a system would help players and coaches to select the optimal combination of rubbers and blade and contain elements of crypto-protection to ensure the security of personal data. To organize the cryptoprotection of the neural network system, an improved method of increasing the speed of implementation of the group matrix cryptotransformation is used. A method of increasing the stability of pseudorandom sequences built on the basis of matrix cryptographic transformation operations was developed by adding them modulo, which ensured an increase in the probability of degenerate transformation results. The use of this method made it possible to reduce the mathematical complexity and time of the cryptographic transformation due to the reduction of the complexity of construction and the use of the inverse transformation. The synthesis of pseudo-random sequences based on the application of matrix cryptographic transformation operations by adding them modulo and statistical analysis of the degeneracy of the transformation results was carried out.

The paper analyzes factors affecting the reliability of informational signals, which may result in distortions in the data regarding emergency indicators of technological parameters in power equipment. We suggest utilizing the fractal-cluster theory framework to describe random informational signals within the informational space, which deviate from standard process parameter characteristics in power station technological processes. We identify fluctuations in the volume of informational three-dimensional phase space, which are characterized by the informational fractal dimension in decimal form. This observation pertains to random information signals with incidental features and demonstrates their correlation with changes in information quality within the informational space. During our research, we defined the analytical expressions facilitating the connection between the enhancement of informational quality, with consideration to deviations from standard process parameters, and variations in the informational dimension of random fractal signals across space coordinates and real-time. Our efforts aim to enhance the reliability of information management systems, software, and hardware in automated process control units during emergency operations of electricity equipment. Such process involves pinpointing reliable information regarding false positives and failures in detecting process parameter deviations. This can be done by tracking changes in electro-value process parameter characteristics in relation to alterations in random signal information within the volume of information space managed by information management systems, software, and hardware in automated process control units, utilizing fractal-cluster theory principles.

The environmental safety of the country is an integral part of national security, which is vital for determining the quality and comfort of conditions for all types of human activity. The paper proposes an assessment of the level of air pollution using geographic information systems in projects of urban environmental management. The problem of assessing the level of environmental safety, namely man-made air pollution by traffic flows, is complex and multifactorial and involves solving a number of scientific and practical problems. These problems are related primarily to defining the source of pollution, as well as to developing a method for quantifying the level of ingredient pollution and visualizing the processes of spatial and temporal distribution of air pollution. Geographic information systems are one of the tools that allow to effectively model the level of air pollution and display its spatial and temporal dynamics. Using geographic information systems, we modeled and visualized the level of air pollution within the metropolis. The results of the study are useful to monitoring the air quality in real time, thus allowing to prevent critical situations in which the concentration of pollutants exceeds the maximum permissible values, identify emission reduction strategies and implement preventive measures.

The study aims to analyse several calculation procedures of safety assessment methods. The research objective of the study is to implement an information technology solution capable of being extensively modified and freely extended with the necessary parameters and variables, depending on the needs. The research object is a safety index assessment of critical infrastructure facilities. The research subject is the modeling utilizing specific safety indices that exhibit linear dependencies. Conversely, indices featuring non-linear relationships necessitate processing through IT software. However, the model’s adaptability and versatility stemming from its classification calculation procedures allow for extensive modification and augmentation with requisite parameters and variables to address varying requirements. The paper systematizes the procedure for obtaining an integral safety index of quality from the construction of safety function matrices. The scope of practical application of the assessment model in safety research can be a universal analytical tool for managing the safety of complex systems of any level.

The article presents the assessment results of the complex efficiency of logistic information and control systems. Increasing the number of trips by public passenger transport requires high quality and efficiency of passenger transportation. Management of logistics systems requires high quality and efficiency in the process of development and practical implementation of organizational, technical, logistical and methodological measures. The efficiency of logistic information and control systems is determined by the possibility of their integration into current transport processes. The use of logistic information and control systems (LICS) based on the use of modern information and computer technologies establishes a comprehensive connection between all participants of the logistics network. The modern scientific approach to modeling the transport technology of passenger transportation indicates that in order to ensure the efficiency of the rolling stock, it is necessary to solve a number of problems. The authors have predicted passenger traffic by public transport using the long short-term memory (LSTM) method . With a sufficient number of network nodes, this type of recurrent neural network architecture can compute any problem, provided that it has a proper matrix of weighting factors, which can be considered as its program. The structure of the LSTM network proposed by the authors for forecasting passenger traffic has four hidden layers and uses the sigmoidal function and the hyperbolic tangent as the activation function.

This publication is a continuation of the authors’ research in the field of transportation system automation. The authors have identified the conditions of influence of the “driver-vehicle-environment” information system (DVE-IS) on the functional state of the vehicle based on preliminary results. The article presents the results of a comprehensive assessment of factors influencing the DVE-IS. Each component of this system functions as a specific separate system, forming in individual subsystems, with specific purposes and functions and its own manifestation of failures in functionality. However, a new type of component failure arise in the process of combining them into one system. Therefore, it is necessary to identify the reasons for failures in the newly formed system and assess their level of influence on the system. The assessment was conducted by comparing the results of a survey of respondents and conclusions of experts in the automotive industry. The publication discusses a comprehensive approach to analyzing the causes and consequences of failures (failure mode and effects analysis (FMEA)) of the DVE-IS using Ishikawa diagrams. Factors leading to failures affect the system during implementation of the information computing system (ICS) for processing vehicle control signals. The author provide a scheme for identifying the interrelationships of failure causes in the ICS at different levels of transmission of control signals of the DVE-IS is provided. A significant result of the research is the discovery of a new structure of ICS levels. Recommendations are provided for a comprehensive quantitative and qualitative assessment of the causes of failures and risks of the DVE-IS.

The paper studies the introduction of information technologies in business processes to develop the information environment of transport enterprises. The authors determine the key aspects of development of information technologies in the business processes of enterprises. The authors also provide their definition of the concept of “information technologies for business process management”. They are defined as a comprehensive set of tools, methods and systems used to support, optimize and control business processes within the framework of forming the information environment of an enterprise or organization. A number of key tasks performed by information technologies for managing business processes of transport enterprises aimed at optimizing and improving the efficiency of their activities have been allocated. The authors have also defined the stages of the implementation process of information technologies for business process management for transport enterprises. Finally, the authors propose a new simulation model of business processes as a tool for developing the information environment of transport enterprises.

The Disability Equality Act states that disabled individuals and their needs should always be taken into account in any civilized society. Free and equal access to digital content and applications is an integral component of today's information and communication society. For those who are blind or visually impaired, however, operating with today's graphical user interfaces (GUIs) is a significant challenge. The development of appropriate computer-based tools and interaction strategies is crucial to address this issue. Navigation mechanisms, orientation aids, and corresponding content preparation are necessary to visually present screen information. Thus, it is important to be able to manage large quantities of information and process it either audibly through voice, or by employing tactile interaction. A Flat Braille display can assist with this task. In this paper, the objective is to determine the degree to which a Flat Braille display facilitates blind individuals’ effective and efficient operation with graphic user interfaces (GUI). To facilitate operation on a tactile area display, the contents should be organized consistently. A brand-new type of tactile window system has been developed to help in achieving this goal. It supports a variety of tactile display types in addition to dividing the output into multiple discontinuous areas. In this regard, we suggest creating a taxonomy that can be useful for the design and the evaluation of these tactile user interfaces as well as the user interactions that occur within them. The proposed taxonomy can aid in the systemic design and evaluation of tactile user interfaces.

The energy market plays a vital role in the development of each country by balancing the production and consumption of energy commodities. Various factors can influence the price of oil or gas, and the disturbances of one variable can instigate short-term, medium-term, or long-term changes in another. Such interconnection between these commodities forms a very complex multiparametric system with trends opposite to the previous dynamics and more predictable periods. Periods of unpredictability characterize the irreversibility of the studied systems, and its loss may be the indicator of destructive processes. Therefore, this article presents indicators-precursors of crisis events which are characterized by the decrease of irreversibility as they occur. The study examines the daily prices of West Texas Intermediate crude oil and Henry Hub natural gas spot prices. The objective is to identify indicators that serve as signs of the upcoming crises in these markets. The estimation of such indicators is based on the algorithms of the natural visibility graph and permutation patterns. In addition, the objective is the construction of a toolbox based on the Python programming language, designed to facilitate the development of indicators of irreversibility using the sliding window procedure. This study proves that the irreversibility of the system can serve as a precursor of financial collapses.

The authors’ analysis of the instantaneous and average values digital tachometer quantization error assessment in the dynamic measurements of angular velocity with an encoder allowed to create an innovative a mathematical model for calculating the critical speed numerical value for an exponential mathematical model that adequately describes the transient process of the electric machine’s operation. The authors discovered that the value of the critical speed depends on the resolution ƶ of the encoder, the quantization frequency $${f}_{0}$$ f 0 , and the duration of the sample time interval $${t}_{0}$$ t 0 , which variation allows to measure the angular velocity with a predetermined normalized value of the quantization error during the transient process of the electric machine from the lower to the upper measurement limit. The practical significance of the proposed approach is as follows. At the beginning of measurements $$n{\le n}_{c}$$ n ≤ n c , the transient characteristics of electric machines are characterized by dips, jumps, synchronous dips in angular velocity, the amplitude and duration of which must be determined with high accuracy. The most effective here is the structure and algorithm of the digital tachometer of instantaneous values. In the section of the transition characteristic, when $$n{>n}_{c}$$ n > n c , such dips are not significant. In addition, the quantization error of instantaneous values also increases with the increase in angular velocity. Therefore, in this section of the transient characteristic, we advise to configure the hardware and software for the tachometer by using an average value.

The paper studies modelling of a flexible manufacturing system that includes several types of processing equipment, a robot for workpiece loading and unloading, and stepping table for loading and unloading. By utilizing a Petri net, the proposed model describes a flexible manufacturing system that consists of a set of equipment states, a set of potential transitions between these states, and linkages between the states and transitions. The authors use tokens to simulate the availability of resources. The generated program, which is intended to determine the ideal sequence of robot action for loading equipment and computing the working cycle time of a flexible manufacturing system, incorporates the mathematical model explained in the paper. The operating principle of the program revolves around logical variables. They are used to model states, whereas integer variables are used to model runtime. The software replicates the cycle one second at a time, and if any transitions are feasible, they are carried out. The future idle time of each component in the flexible manufacturing system is predetermined. Based on this data, the subsequent actions of the system components are created, and then utilized to perform certain checks. Examples of the program used to model two- and three-machine systems are provided in the paper. The flexible manufacturing system's functioning can be optimized, and the expenses associated with switching it over can be decreased, by implementing this software in production. In addition, the paper demonstrates the usefulness and application of Petri nets for simulating the functioning of flexible manufacturing systems through information technologies.

The article analyzes the development of specialized software for predicting PM2.5 and PM10 air pollution levels using an artificial intelligence approach. The core objective is to develop an algorithm and its corresponding software based on neural networks. This software aims to quickly and accurately analyze air quality with high accuracy and speed within specific urban or industrial zones, focusing on particulate matter with diameters of 2.5 and 10 µm. This predictive capability will ultimately affect the decision-making processes to mitigate or minimize air pollution levels. The study focuses on the development of the prediction algorithm itself (object) and the relevant software utilizing neural networks to achieve this goal (subject). The chosen XGBoost models (XGBoost-linear-regression and XGBoost-mlp) demonstrate exceptional accuracy (average absolute error below 1.47%) and efficiency, paving the way for informed actions to lessen the environmental and public health impacts of air pollution.

The aim of this work is to enhance the design of an actuator for a miniature flying insect-sized mini-robot by developing a new method of controlling its wings using a piezoelectric air emitter. The relevance of this research is associated with the development of a new method for controlling the wings for a miniature flying insect-sized mini-robot, as well as the creation of a new type of actuator unit for this purpose. A model of an actuator for flying miniature robots based on a piezoelectric air emitter has been proposed and developed for the first time. Additionally, experimental prototypes have been created, and experimental investigations of the new actuator unit based on the piezoelectric air emitter have been conducted.

The work is devoted to the creation of an information model of the knowledge base as a set of knowledge through the relationship of high-quality metallographic images of fine-grained macro- and microstructures of the weld, the collar zone of laser butt welding of thin-walled structures and methods of controlling the crystallisation of molten metal, which are used to collect, store, update and use them, as well as means of managing all these processes. The study was conducted on the basis of computer-experimental modelling using the proposed method of laser welding of butt joints of thin-walled structures. The aim of the study is to form an information efficient model of the knowledge base by visualizing the schemes of relations of high-quality metallographic images of fine-grained macro-, microstructures of the weld and the collar zone of laser butt welding of thin-walled structures, distributions of the main components (Fe, Cr, Ni) and microhardness in the structures of welds, and the developed three methods of controlling the crystallization of molten metal, which create conditions for the formation of the maximum number of crystallization centres and minimization of the linear velocity of the weld. The object is the processes of knowledge formation through the accumulation, storage, updating and use of knowledge. The subject of the study is an effective knowledge base through metallographic images of laser welding microstructures in small-scale production. The research methods: information technologies for collecting, processing, storing information and control systems; visualisation; algorithms; decision-making in the conditions of unforeseen factors of small-scale production. Conclusions: An information-efficient model of the knowledge base is proposed, which is formed on the basis of relational relations of metallographic images, distributions of the main components and microhardness.

This paper analyzes the results of modeling of piezoelectric elements with different shapes and different sets of material constants. This modeling is capable of determining the electrical impedance of a piezoelectric ceramic sample in the mode of harmonic oscillations. The aim of this study is to research the procedures of mathematical modeling for variously configured piezoelectric components intended for devices used in information, communication, and robotic systems and to delve into the key electromechanical characteristics of these components. The object of the research is the process of mathematical modeling of differently configured piezoelectric elements; the subject of the research is mathematical models of piezoelectric elements.

The article presents the results of the development of a new information technology for analysing and processing experimentally obtained data on electric fields, as well as testing the information and measuring system created on its basis to determine and study the power and energy characteristics of low-power electric fields arising in various microelectronic devices. The work aim to develop an information technology based on an information-measuring system that allows for high-precision research of the characteristics and visualisation of the distribution of ultra-low-power electric fields in real time. The research object is the high-precision study of the characteristics of electric fields of ultra-low power; the research subject is the information technology for processing data on electric fields, calculating the power and energy characteristics of these fields and visualising the results. The authors have developed a new information technology for analysing and processing experimentally obtained data on ultra-low power electric fields arising in microelectronic devices. The developed information technology has found practical application in the information-measuring system (specifically, it increased accuracy (up to 4.5–7.5%) and adequacy of determination and study of electric field characteristics). It also enables a detailed study and prompt acquisition of the exact data related to distribution of electric fields of ultra-low power on the surface in real time, reduces the feedback time by 28–32%, increases the measurement accuracy by 8.5–13%, increases the speed of research by 35–40% and guarantees high reliability of the equipment.

The research developed a geoinformation satellite monitoring technology for quantitative assessment of atmospheric air pollution over the territory of Ukraine. The technology is universal and allows for prompt monitoring of all greenhouse gases. This article is devoted to the complex geoinformation monitoring of sulfur dioxide. The research used data on the concentration of sulfur dioxide for 5 years: from 2019 to 2023 from the Sentinel-5P satellite product OFFL SO2 processing level L3. The Google Earth Engine (GEE) geospatial processing service was used to calculate and obtain remote sensing data. With the help of the ArcGIS geoinformation program, maps of SO2 distribution on the territory of Ukraine and adjacent territories were constructed. Regional areas with anomalous SO2 content values and transboundary SO2 transfer were identified. Using the comparison of satellite and ground measurements, a comparison graph was made between these observations, and 4 aggregates were selected. The integrated use of satellite and ground data allows for a significant increase in the informativeness of the proposed technology.

The paper analyzes the development of innovative models and methods for detecting and distinguishing signals in non-Gaussian noise. The authors propose a new quality criterion for statistical hypothesis testing, based on describing the random process through its moments. The paper suggests the use of stochastic polynomials to develop decision rules, where the optimal coefficients are determined by the new adapted moment quality criterion for multiple hypothesis testing. The paper provides an analysis of the synthesized models and polynomial algorithms used for detecting and distinguishing signals in non-Gaussian noise. A generalized structure of polynomial decision rules for multiple statistical hypothesis testing is suggested. The paper highlight the fact that nonlinear processing of samples, considering parameters of non-Gaussian distribution of random variables such as moments of the third and higher orders, can improve signal processing efficiency. This paper also explores the development of effective methods and algorithms for processing data in non-Gaussian noise. Research has demonstrated that the enhanced effectiveness of nonlinear signal processing, relative to existing results, is contingent upon accounting for the characteristics of non-Gaussian noise.

ORCID is a unique identifier for researchers that helps to connect their research outputs and activities. Integrating Digital Repositories with ORCID can provide several benefits for researchers and institutions, including improved visibility and impact of research, facilitated collaboration, and accelerated scientific discovery.There are two main ways to integrate a Digital Repository with ORCID: using third-party services or developing in-house solutions. The best approach will depend on the size and complexity of the Digital Repository system and the available resources and expertise.The integration of Digital Repositories with ORCID can be a complex process, but the benefits are significant for the research community. Resources are available on the ORCID website and through third-party services to support organizations interested in undertaking the integration process.By leveraging the support of the ORCID consortium and the State Scientific-Technical Library of Ukraine, organizations can navigate the integration process and contribute to a more robust research ecosystem.

Wastewater treatment is a critical process that safeguards the environment, prevents pollution, and protects public health. Its success is highly dependent on multiple factors, including wastewater characteristics, treatment process design and construction, operation parameters, maintenance practices, etc. Treated wastewater quality must satisfy the requirements for safe disposal according to the regulatory authorities. One of the options for efficient wastewater treatment is a combination of biological treatment and membrane separation, combining an innovative approach and high treatment performance. However, such a system requires strict control to deliver the best result. Optimisation of this process requires a vast amount of data. Utilization of a Programmable Logic Controller (PLC) and Supervisory Control and Data Acquisition (SCADA), as well as laboratory analyses, can assist in collecting the required data.

Assessing the risk of an enterprise bankruptcy based on the analysis of its finances is not enough, because when problems within the company arise at the financial level, it is often too late to fix them, thus making bankruptcy inevitable. It is, however, possible to substantially improve the approach to the analysis of the enterprise bankruptcy risk by combining the accounting of quantitative (financial) and qualitative indicators, and considering them not only in statics, but also in dynamics. To timely identify the crisis at the enterprise, it is important to assess the probability of its bankruptcy beforehand. Generally, quantitative and qualitative indicators, calculated based on financial statements, which do not fully meet the requirements of an objective assessment of enterprise business processes, are used in operating models for determining the risk of enterprise bankruptcy. A significant increase in the efficiency of the analysis of the enterprise bankruptcy risk level can be achieved by combining the accounting of quantitative (financial) and qualitative indicators, and considering them not only in statics, but also in dynamics. However, the existing methods, for example Multiple Discriminator Analysis Methods, do not provide such a possibility. We advise to use an approach based on the use of a fuzzy set of devices to predict the bankruptcy of Ukrainian enterprises, while taking into account the disadvantages of existing quantitative and qualitative approaches and giving an opportunity to more objective estimation of the actual state of the enterprise. The purpose of the study is to develop an information technology and implement it as a web-oriented service for solving the task of assessing the enterprise bankruptcy risk online based on the apparatus of fuzzy sets, which is the foundation of the proposed methodology, built on the business process approach. This approach provides an opportunity to identify the symptoms of the crisis in each business process, their impact on the company's activities and develop countermeasures to prevent bankruptcy.

The purpose of the study is to identify the comparative advantages of using specialized software for the sensitivity analysis of the enterprise value to the factors that determine the variability of discounted cash flows. The research object is the method of sensitivity analysis and the peculiarities of its implementation. The research subject is a comparative description of the ways of implementing the method of risk sensitivity analysis, with the identification of the results of the impact of changes in each individual parameter of the financial model and the impact of simultaneous stochastic changes in various parameters of the financial model on the key value indicator. Research methods include enterprise value estimation based on discounted cash flows, sensitivity analysis, and simulation modeling. The authors used several software functions during the research, namely predictor, define assumption, define forecast, simulation of changes in financial model parameters, sensitivity analysis. The results are presented in the form of recommendations for a better way to perform sensitivity analysis of the cash flows present value to changes in the parameters of the DCF model.

In the pressure driven membrane processes the flow characteristics have a significant influence on the intensity of mass transfer and concertation polarization, and also on the pressure drop in apparatuses. With the development of the information theologies, computational fluid dynamics (CFD) methods became the widely used technique for the analysis of the flow regularities in such systems. The object of this study is the fluid flow process in the channels of the membrane module. The subject of this study is the hydrodynamic parameters of the flow and the geometrical parameters of the channel. In the study, we compared of the flow characteristics, primarily the pressure drops, in the hypothetic channels of the spiral wound membrane modules, in the absence of a spacer, for the cases of ring-shaped and plate geometrical shapes. We used the package CFDOF for the design system FreeCAD for the analysis. The results of the simulation show that the difference in the pressure drop for two geometrical shapes does not exceed 3.2%, which indicates that the conditional unwinding of the membrane module in the plane is an accurate enough approximation for the considered hypothetical conditions.

This study focuses on proving the effectiveness of computer modeling for strengthening structural elements made of optical glass using electron-beam technology. This technology allows for enhancing the strength of structural elements such as windows for submarines and surface vessels, aircraft, objects in space, and so on. The protective shell of an infrared surveillance device is a spherical meniscus. The strengthening effect of the spherical meniscus is achieved through the electron beam processing of certain areas of the surface where significant tensile stresses occur. Prestressed regions of increased strength are created in the near-surface layer at the processing sites. The article presents a computer model of meniscus strengthening mechanics. To accomplish this, the authors employ a theory of spatial axisymmetric bodies developed by them. Using the “INTEGRAL-SV” software package, the areas of meniscus surface processing by the beam are determined. A numerical analysis of the stress-strain state of the processed meniscus under the action of introduced compressive stresses in the strengthened near-surface layer is conducted. Stresses in the strengthened near-surface layer is conducted. The authors then prove the safety of the consequences of electron beam processing for the meniscus. Afterward, a numerical experiment on the impact of meniscus processing on its strength is carried out, thus allowing the authors to demonstrate the effectiveness of computer modeling in solving strength problems.

The paper discusses the phase method for solving a second-order differential equation, particularly the equation for eigenfunctions and eigenvalues of the Hamiltonian operator, i.e., the Schrödinger equation. The classical phase method is adapted to a problem containing two different regions with corresponding parameters. This method is implemented using computer algebra systems (Wolfram Mathematica). The modified method is applied to compute the electronic energy spectrum of an electron in a spherical quantum dot for cases of rectangular confining potential and smooth potential. For the rectangular potential, exact solutions of the corresponding Schrödinger equation exist, so they are compared with the results obtained from the proposed method, showing high accuracy in convergence. The advantage and value of the method lie in its applicability to spherical quantum dots, both single-layer and multi-layer, with arbitrary confining potentials.

The research aims to create the foundation for computer modeling of the optimal chemical composition of polyamide-6 waste agglomerate with increased set of strength properties. The research tasks are identifying the optimal chemical composition of modified polyamide waste agglomerate and building computer models for forecasting their most important performance characteristics. The research is modified polyamide waste agglomerate based on polyamide-6, MW-PA CB10 masterbatch and humic acids. The research subject is computer modeling processes of optimal chemical composition of modified polyamide waste agglomerate. The research method is computer simulation in MathCad Prime 6.0. The authors developed models for forecasting the performance properties of modified polyamide waste agglomerate depending on their chemical composition were built, which can be adapted to any content of MW-PA CB10 masterbatch and humic acids. It was established that the polyamide-6 waste agglomerate with 2% wt. of masterbatch MW-PA CB10 has the best properties. The impact strength for this composition is 43.5 MPa, breaking stress during bending is 126.4 MPa, tensile strength is 342 N and elongation at break is 117%. The authors recommended utilizing the same composition in traditional fields of primary polyamide-6, such as manufacturing of engineering and technical goods.

The development of a municipal information system is necessary for effective monitoring of the soil environment quality of the city. Various geographic information systems (GIS) are the most convenient and powerful tools for processing data since they have both spatial and semantic binding. This technology combines traditional database operations, such as querying and statistical analysis, with the benefits of full visualization and geographic (spatial) analysis provided by a map. The object of the study is the evaluation of the parameters of the ecological condition of the soils’ condition in Cherkasy according to the data of operational monitoring of pollution. The subject of the research is information technology, methods, algorithms and software and technical means of automating the evaluation of parameters of substance emissions based on the data of operational monitoring of soil cover pollution. The authors performed the zoning of the city territory was carried out according to the buffer properties of the soil using the SURFER software package. The acquired results possess high practical significance for the development of geoecological monitoring of the urbanized territory, as well as for the ecological management of the city.

Today, unmanned vehicles handle the complexities of real-world driving under simple road conditions much better than the average driver. However, a fully autonomous autopilot that does not require human intervention remains confined to test sites. This limitation exists due to the need to ensure its adequate response in the most challenging road situations. In this study, we propose using computational aerodynamics methods to study how changes in air pressure, caused by aerodynamic flows from other vehicles and wind at various angles to the vehicle’s direction, affect vehicle stability. The calculated data enable us to assess the influence of these factors on traffic safety and to integrate them into the machine learning tasks for vehicle artificial intelligence.