bluuebunny/crossref_metadata_2025 huggingface dataset:
ТЕХНОЛОГІЧНІ АСПЕКТИ ТОРЦЕВОГО ФРЕЗЕРУВАННЯ СТАЛЕЙ ВИСОКОЇ ТВЕРДОСТІ КУБІЧНИМ НІТРИДОМ БОРУ
Authors: АНТОНЮК ВІКТОР
Published: January 2025

The article presents the results of a comprehensive analytical study on the influence of various face milling parameters on the machinability of high-hardness steels. The focus is on the use of polycrystalline cubic boron nitride (PCBN) tools, both uncoated and coated, which demonstrate high wear resistance and stability when machining hard-to-machine materials. The analytical studies include the analysis of the effects of cutting parameters, such as cutting speed, depth of cut, and feed rate, as well as cooling and lubrication methods on the quality of the machined surface and the wear resistance of the tools. The use of PCBN tools from different groups with varying geometries significantly improves process productivity and reduces maintenance costs due to their ability to withstand high temperatures and high mechanical loads. The experiment compares the effectiveness of PCBN tools from different groups. It has been shown that PCBN tools provide better surface quality and exhibit less wear under high-speed milling conditions. The study also considers various cooling methods and their impact on the wear resistance of the tools and the quality of the machined surface. Special attention is given to optimizing face milling parameters to achieve maximum process efficiency, particularly reducing surface roughness of high-hardness steels. Recommendations have been developed for selecting optimal cutting regimes that minimize tool wear and improve surface roughness. The article also explores the prospects of introducing new technologies and materials into production, which can significantly impact the efficiency of face milling high-hardness steels. The presented analytical research results can be valuable for engineers and technologists involved in the development and improvement of machining processes for hard materials to further enhance surface roughness in face milling.
СТВОРЕННЯ ПРОГРАМНОГО ЗАБЕЗПЕЧЕННЯ ДЛЯ МОДЕЛЮВАННЯ СЕЗОННОСТІ В ЧАСОВИХ РЯДАХ
Authors: ДЕМКІВСЬКА ТЕТЯНА , ЧУПРИНКА НАТАЛІЯ , ХОЛОД АРТЕМ
Published: January 2025

The main objective of this work is to create a software tool for generating forecasts for processes that can be described by time series and that have a seasonal effect based on additive and multiplicative models We analyzed processes predictable by these models. At the outset, modeling was undertaken in Microsoft Excel. The built model is used as a control example to check the correctness of the developed software. To begin with, this time series was analyzed for variability using the coefficient of variation. Since its value exceeds 33%, namely 36%, a multiplicative time series model was chosen for forecasting.
Based on the analysis of the visual presentation of changes in the measured values of the farm's profit, it can be concluded that the data of the series indicate the presence of a pronounced trend and seasonal effect, which indicates an increase in income in the 4th quarter. The work describes step-by-step instructions for building a model and building a forecast. The trend parameters were found using the least squares method. To build a forecast, we multiply the trend by the seasonal component. Analysis of the generated forecast graph demonstrates the model's ability to replicate the dynamics of the input time series.. The adequacy of the built model is confirmed by the coefficient of determination, the value of which is 96,32%.
To automate forecast calculations in the Visual Studio Community 2022 environment, using the additional .NET Framework platform, a forecast calculation window program based on the additive and multiplicative time series model for Windows has been developed. C# was utilized to develop. An initial view of the functionality of the program and a form illustrating the final demonstration of the capabilities of the developed software are provided. A forecast and a confidence interval for the forecast for the next quarter have been constructed.
 The capabilities of the ready-to-use developed software product are demonstrated.
ОЦІНКА РИЗИКІВ ТА ЇХ ВПЛИВ НА ЖИТТЄВИЙ ЦИКЛ РОЗРОБКИ ПРОГРАМНОГО ЗАБЕЗПЕЧЕННЯ
Authors: ЛІЩИНА НАТАЛІЯ , БОЙКО ЛЕВ , ГУЛЬЧУК ЮРІЙ
Published: January 2025

Modern software development is accompanied by numerous challenges associated with risks at all stages of the product lifecycle: from design and development to operation and support. Risks in software development can include technical (technological obsolescence, unstable requirements), managerial (insufficient communication, limited budget), and operational (errors, failure to meet user expectations). These risks directly affect the quality, timing, and budget of development, as well as the overall competitiveness of the software. Risk assessment and management are among the key scientific and practical tasks aimed at ensuring the efficiency of software development and implementation.
This article analyzes the main risks that arise at different stages of the software development life cycle and presents modern methods of their identification and management.
The author explores the risks associated with planning, requirements analysis, design, development, testing, implementation, and support of software products. The author identifies specific risks for each stage and suggests ways to minimize them.
The article discusses in detail the main groups of risks that may arise at different stages of software development: planning, requirements analysis, design, development, testing, implementation, and support. Various methods of risk assessment are considered, such as decision tree analysis, forecasting, risk matrices, the Five Whys technique, and SWOT analysis. Effective methods of risk management are presented, including resource reservation, improved communication, staff development, use of flexible development methodologies (Agile, Scrum), and others.
The paper emphasizes the importance of an integrated approach to risk management, which includes both the identification and assessment of risks and the development of effective strategies to minimize them. The methods and approaches proposed in the article can be used by project managers, developers, and other stakeholders to improve the efficiency of software development and reduce the risk of project failure.
NAIVE RULE-BASED METHOD IN SENTIMENT ANALYSIS OF UKRAINIAN-LANGUAGE CONTENT
Authors: LOMOVATSKYI ANTON , BASYUK TARAS
Published: January 2025

This paper deals with the obstacles faced while executing the Naive Rule Based algorithms for analyzing sentiment of Ukrainian language content. Text sentiment analysis is useful to such types of content as feedbacks, brand tracking, political stances and psychological analyses. A number of steps, which include the previously described treatment of text, explication of elements of the text, emojis, links, hashtags and other special characters are abandoned within this work. The next step tackles ‘tokenization’ where the text is broken into a set of small units or words and ‘lemmatization’ where words are worn down to the basic word form for the purpose of analyses. After these steps are taken care of, a sentiment lexicon is used to classify the text in terms of its tone i.e. positive, negative and neutral. Even though it is very basic, the Naive Rule-Based method stands out for its simple and effective approach for carrying out sentiment analysis, ideal for scenarios in which more advanced and complex machine learning techniques may not be possible owing to data, computing power, and time limitations. This technique makes it possible to carry out easy customization and even use of domain specific language by simply expanding the sentiment lexicon or changing the rules. Nevertheless, there are some aspects in which the method falls short. More complex properties of language such as sarcasm, the meaning within context, and building up deep complex sentences are all aspects that the system can struggle with and therefore limit its accuracy. This study proposes some useful recommendations to address the limitations, including extending the existing emotion lexicon so more emotions can be comprehended, and the implementation of context-embedded methods. Further, hybrid methods that combine conventions and rules in addition to machine learning approaches are identified as prospects for improving the effectiveness. One such case study demonstrates the effectiveness of the Naive Rule-based approach as applied to the dataset in the Ukrainian language. The results demonstrate the capability of the method to provide clear sentiment scoring and emotion classification. Although this approach is not at the level of machine learning models, it still manages to be an efficient and feasible approach for specific use cases especially in cases where speed and clarity take precedence. The findings of this study emphasize that, in resource-poor settings, sentiment analysis can be carried out using this technique with data processing tools and methods that have low precision and context dimensions, and more ways to enhance accuracy and context dimensions are provided.
МЕТОД ВИЯВЛЕННЯ ЦІЛЬОВИХ ОБ’ЄКТІВ ПРЕДМЕТНОЇ ОБЛАСТІ У ТЕКСТОВОМУ КОНТЕНТІ
Authors: МАЗУРЕЦЬ ОЛЕКСАНДР , ВІТ РОМАН
Published: January 2025

Method for detecting subject area target objects is proposed, which uses machine learning algorithms for adaptive object recognition, taking into account the specifics of the subject area, which allows to significantly reduce the time of data processing and reduce the risk of losing important information. The method for detecting subject area target objects allows to transform input data in the form of the researched text and a pre-processed and balanced corpus of texts of the researched subject area into output data in the form of a formed set of target objects from the researched text, which is a combined set of keywords found by various methods without repetitions and the set of NER grouped by lemmatization. The proposed method for detecting subject area target objects differs from the existing ones by taking into account keywords and noun entities of the subject area, which made it possible to increase accuracy of detection of detecting subject area target objects as result of taking into account noun entities.
To research the effectiveness of developed method for detecting subject area target objects, a training dataset of 400 texts in the Ukrainian language was formed. Also, for the validation of proposed method, the software was developed to convert the text content of files from the test sample into a set of target objects of the subject area; separate console software was created to use the obtained list of target objects for the studied texts and dictionaries from the subject areas selected according to the dataset. The performed study of the effectiveness of the developed method for detecting subject area target objects revealed that the target objects of the subject areas found by the method are able to perform the further task of classification, demonstrating on the metric of Euclidean distances the grouping of texts of the same category and the increase of the distance orthogonal to it. This determines the beneficial effect and scope of the developed method.
МЕТОД ВИЯВЛЕННЯ ОБ’ЄКТІВ ПРОПАГАНДИ НЕЙРОМЕРЕЖЕВИМИ МОДЕЛЯМИ ГЛИБОКОГО НАВЧАННЯ З ВІЗУАЛЬНОЮ ІНТЕРПРЕТАЦІЄЮ ПРИЙНЯТИХ РІШЕНЬ
Authors: МОЛЧАНОВА МАРИНА
Published: January 2025

The present work proposes the method of identifying propaganda objects by neural network models of deep learning with visual interpretation of the decisions, which differs from the existing ones by expanding the plural of propaganda objects by adding variants of their verbal submissions and using context windows to identify connections between the used methods and objects of propaganda, which made it possible to improve the results of detecting objects of propaganda and visually interpret them.
The main stages of implementing the method of identifying propaganda objects by neural network models of deep learning with visual interpretation of the decisions made are the formation of a plural of propaganda objects by recognizing named entities, pre-processing of the text and expansion of the plural of propaganda objects by adding variants of their verbal representations, building contextual windows for verbal presentations of each object of propaganda, taking into account the threshold value of the minimum window size, assessment of the level of used propaganda methods within context windows according to neural network models, and building the plural of important connections between methods and objects of propaganda, taking into account the threshold value of the minimum level of ostent of propaganda.
The effectiveness of using the proposed the method of identifying propaganda objects by neural network models of deep learning with visual interpretation of the decisions has been experimentally proven, which allows, unlike existing analogues, in addition to searching for NER using the "STANZA" neural network library, also expanding the plural of available propaganda objects in texts using the "FastText" machine learning library, as well as issuing an assessment by which the objects found are correlated with the propaganda methods used. For ease of use, the visual interpretation of the found objects of propaganda is also provided, which allows to visually observe the objects of influence within the framework of the used propaganda methods.
ЧИННИКИ ПОЛІПШЕННЯ ЗАХИСТУОПТОЕЛЕКТРОННИХ ПРИСТРОЇВ - СОНЯЧНИХ БАТАРЕЙ
Authors: НАКАШИДЗЕ ЛІЛІЯ , МАЗУРИК СТАНІСЛАВ , КОРСУНСЬКИЙ РОДІОН
Published: January 2025

The work presents a study of the physical and technological approach to the solar panels protection to prevent local overheating of electrical origin, which occur because of mismatch of photocurrents in serial connections of solar elements. It is determined that the currently used widely known methods lead to a significant increase in the massive parameters of photoelectric installations. Modern methods of protecting solar installations, such as the use of diodes or active protection systems, are not universal approaches to solving the problem. Therefore, the approach is relevant to the authors on the development and research of solar protection methods. Thus, it is advisable to use polymer-composing devices, which similarly to traditional fuses, limit the flow of dangerously high reverse current during the inconsistency of electrical indicators in the solar panel. The work conducted the study that determines the effect of self-renovation polymer-composing fuses on photoelectric characteristics of the solar battery. In addition, there was done analysis to determine the prospect of using PPTC-cards as elements of thermal protection of solar panels. It has been found that polymer composites are capable of functioning as multiple fuses that do not affect the solar battery and are able to effectively isolate solar elements by performing the function of transition into an inferior state in emergencies associated with the heating of the P-N structure of the photoelement. It is experimentally established that polymer-composing fuses are able to effectively isolate the solar elements, turning to a low-conduct in emergencies associated with the heating of the solar element. The prospects of the solar panel with a two -layer structure of the polymer composite and the solar element in commercial installations are analyzed. In particular, the long-term return of fuses to a high-conducting state and a high temperature of the beginning of the phase transition of the material, which limits the use of polymer-composing fuses for electric heat protection of solar cells, especially in regions with temperate climates.
АЛГОРИТМ МОДЕЛЮВАННЯ СИГНАЛЬНИХ ПЕРЕТВОРЮВАЧІВ ІМПЕДАНСУ ДЛЯ СЕНСОРНИХ ПРИСТРОЇВ
Authors: БАРИЛО ГРИГОРІЙ , ПАВЛЕНКО МИХАЙЛО , АДАМ’ЯК ОЛЕГ , НИКОН ОЛЕГ , СОРОКА ВЛАДИСЛАВ
Published: January 2025

This study focuses on the development and application of a SPICE modeling algorithm designed for impedance spectroscopy circuits. Impedance spectroscopy is a method widely utilized in sensor technologies and data fusion systems to measure and analyze complex electrical properties. The paper emphasizes the need for advanced modeling techniques that improve the accuracy and reliability of signal conversion in sensor networks and mixed-signal electronics. The developed algorithm leverages modern SPICE macromodels, such as the Differentiator Macro, Multiplier Macro, and Integrator Macro, to simulate active (ZRE) and reactive (ZIM) components of impedance with high precision. These components are crucial for analyzing Nyquist diagrams, which graphically represent impedance in the complex plane.
The proposed modeling approach addresses key challenges in impedance measurement, including frequency modulation and the influence of circuit component parameters on signal characteristics. By employing parametric analysis, the algorithm enables researchers to investigate the impact of operational amplifier Gain Bandwidth (GBW) and other critical parameters on the accuracy of impedance measurement. The study presents practical examples demonstrating the algorithm's application to a quadrature detector—a key element in impedance conversion circuits. Results indicate that signal conversion accuracy significantly improves with GBW values of operational amplifiers exceeding 1E7 Hz, underscoring the importance of selecting high-quality components for circuit design.
The versatility of the algorithm lies in its ability to simulate a broad range of operational conditions and to optimize circuit performance by adjusting component specifications. This capability is particularly relevant in the context of modern sensor systems, where reliability and precision are paramount. The findings contribute to the field of mixed-signal electronics, providing a robust framework for analyzing and designing advanced impedance spectroscopy circuits. This research paves the way for further innovations in sensor technology and data fusion systems, where accurate impedance measurement is essential for achieving high-performance functionality.
МЕТОД СЕГМЕНТАЦІЇ МРТ СЕРЦЯ НА ОСНОВІ ЛОКАЛІЗАЦІЇ МАСОК
Authors: СЛОБОДЗЯН ВІТАЛІЙ , БАРМАК ОЛЕКСАНДР
Published: January 2025

MRI analysis of cardiac images is a time-consuming process that requires significant effort and time. This is due to the complexity of cardiac anatomy, the variability of images, and the need for high accuracy in detecting pathologies. Automation of MRI analysis processes is important for improving diagnostic efficiency. High-quality segmentation of MRI cardiac images can serve as a basis for further research and clinical applications.
This study proposes a novel approach to myocardial segmentation in MRI images, which includes three stages: localization, mask generation, and post-processing. The first stage involves the decomposition of masks into separate binary masks for myocardium, left and right ventricles. The second stage involves detailed mask generation based on localized images to ensure accurate determination of the contours of the heart structures. The third stage involves post-processing of the masks to smooth transitions between pixels and preserve details when resizing the image.
To evaluate the accurancy of the results obtained, a series of experiments were conducted using the Automated Cardiac Diagnosis Challenge dataset. Using the proposed approach, it was possible to achieve an accuracy of segmentation of the right ventricle of 0.974, the left ventricle of 0.947, and the left ventricular myocardium of 0.896 for End diastole and the right ventricle of 0.94, the left ventricle of 0.915, and the left ventricular myocardium of 0.92 for End systole.
The proposed approach has the potential for widespread use as a basis for further MRI image research, ensuring the accuracy of cardiac segmentation in MRI images.
МЕТОД ІНТЕРПРЕТАЦІЇ РЕЗУЛЬТАТІВ ВИЯВЛЕННЯ КІБЕРЗАЛЯКУВАНЬ У ТЕКСТОВОМУ КОНТЕНТІ ЗАСОБАМИ ШТУЧНОГО ІНТЕЛЕКТУ
Authors: СОБКО ОЛЕНА
Published: January 2025

The article proposes the method for interpreting the results of cyberbullying detection in textual content by means of artificial intelligence, which is intended to explain the decisions of the neural network model regarding the types of cyberbullying identified in the textual content. The method is original in that it interprets the results for each detected type of cyberbullying separately, which is achieved by using a multi-label classifier of a transformer neural network architecture and an interpretation model of a machine learning model. By using the trained BERT neural network model for multi-label classification of cyberbullying types in the input text sample, different types of cyberbullying are detected with the percentage of each of them. According to the developed method, an approach based on the use of a machine learning model for the local interpretability of LIME models is used for the visual interpretation of the results of cyberbullying detection, which allows you to visualize the impact of the use of individual words on the model's decision regarding whether the text belongs to different types of cyberbullying.
The developed method provides three views of the interpretation of the results of cyberbullying detection: interpretation of the results according to the color palette, interpretation of the results according to the diagrams of the local importance of words, interpretation of the results according to the diagrams of the general importance of the words. The interpretation of the results according to the color palette consists in using the absolute value of the weights to determine the brightness of the color, where the brightest color indicates the greatest influence of the word on the decision made by the model, and the least bright color indicates the smallest influence, regardless of whether this influence was positive or negative. The interpretation of the results based on the diagrams of the local importance of words is provided by constructing diagrams of the influence of individual words of the text on the probability of assigning this text to a specific type of cyberbullying, which allows you to see how the model evaluates the weight of each word in the text depending on its contribution to the model's decision. The interpretation of the results from the charts of the overall importance of words is provided by forming a set of 10 words that the model considers important regardless of the specific type of cyberbullying.
The results of the experiments showed that the created method provides interpretation of decisions regarding the results of neural network detection of cyberbullying at a level sufficient for a person to understand the features of the text, which resulted in decision-making by artificial intelligence regarding the detection of types of cyberbullying.
АНАЛІЗ МОДЕЛЕЙ ДІАГНОСТИКИ ДЛЯ ВИЗНАЧЕННЯ ТЕХНІЧНОГО СТАНУ ТРАНСПОРТНИХ ЗАСОБІВ
Authors: БУРЛАКА СЕРГІЙ , МИТКО МИКОЛА , БОРИСЮК ДМИТРО
Published: January 2025

The types of diagnostic models include the diagnostic object, which can be in a functional state and meet all technical requirements at that specific moment in time. The functional state, along with all operational states of the diagnostic object, reflects its true technical condition. Therefore, to achieve this goal, diagnostics can only result from the analysis of numerous functional and malfunctioning states in which the object being studied, particularly in a vehicle, may exist. Accordingly, the analysis can be conducted theoretically during the development phase of a new car and its components, or experimentally during the research and operation of the vehicle.
However, when conducting such experiments in operation, difficulties arise due to the large number of possible states of the diagnostic object, or simply due to technical infeasibility for complete execution. In this regard, special methods are required for the theoretical analysis of many possible states of the vehicle, both as a whole and for its individual parts. Such methods are based on the investigation of diagnostic models, which in turn contribute to enhancing the reliability and safety of vehicles.
This article specifically analyzes diagnostic and analytical models, discusses simulation modeling, and focuses on parameters and standards, explaining what technical condition parameters are and providing an example of a structural-causal diagnostic model for vehicles.
It addresses various diagnostic indicators and defines diagnostic parameters, emphasizing that these parameters must possess sensitivity, unambiguity, stability, and informativeness regarding the identification of causal relationships with structural parameters. The diagnostic parameters consist of two groups and are determined by standards, as well as governed by the normative and technical documentation from manufacturers.
СИСТЕМА ПЕРЕВЕЗЕННЯ ЗАМОВЛЕНЬ ПОВІТРЯНИМИ ТРАНСПОРТНИМИ ОДИНИЦЯМИ (ДРОНАМИ) У ДИНАМІЧНІЙ МЕРЕЖІ
Authors: МІХАЛЕВCЬКИЙ ВІТАЛІЙ , СКРИПНИК ТЕТЯНА , ТИМЧУК МАРІЯ
Published: January 2025

The article proposes an approach to the transportation of orders by air transport units (drones) in a dynamic network. The issue of using drones as transport units in the logistics sector is becoming more important every year. The growth of technology forces various types of enterprises and organizations to engage in the use of modern information and technical support in order to meet the needs of their enterprise and compete with their opponents. Therefore, one of the next steps in transport logistics may be the use of drones and accompanying software for their management. The idea of ​​implementing air delivery of orders is currently only at the stage of formation and its successful application depends on a list of factors, one of which is the use of software for optimal system operation.
The principle of operation is as follows: the company provides an open API service for creating a delivery request both by an ordinary user through an application, website or physical branch, and for entrepreneurs and companies to integrate the API with their service. The logistics system assumes the presence of centers, where each has a certain number of vehicles (drones), their current unit ready for work, maximum and involved in the work quantity.
The direction of practical use of the developed method and tools is the automation of the selection of the optimal order delivery route in a dynamic network based on cloud technologies.
АНАЛІЗ РЕГІОНАЛЬНИХ ТРАДИЦІЙ УКРАЇНСЬКОЇ ВИШИВКИ ТА ЇХ СЕГМЕНТАЦІЯ З ВИКОРИСТАННЯМ ЦИФРОВИХ ТЕХНОЛОГІЙ
Authors: НАДОПТА ТЕТЯНА , ЄРІЙ АНДРІЙ , АНДРЄЄВА ОЛЕНА , СКІДАН ВЛАДИСЛАВА , ЗУБКО ГАННА
Published: January 2025

The paper presents the results of the analysis of the reflection of regional traditions in Ukrainian embroidery and their implementation in the modern design of traditional clothing. The question of the transformation of Ukrainian embroidery in the conditions of European integration, globalization and modern requirements is considered. The method of adaptation of Ukrainian traditions in modern design solutions is defined and the tool of their implementation in practical activity is proposed. The process of globalization in Ukraine is an important stage of transformation of political, economic systems and public consciousness. An important aspect of this process is the preservation of cultural heritage, in particular, the art of embroidery, which is an integral part of the national identity of the Slavic peoples. Ukrainian embroidery, based on ancient rites and symbols, reflects the local characteristics of different regions of Ukraine and plays the role of a social code that carries centuries-old traditions that are traced in the process of the evolution of patterns on the embroidery. It has deep historical roots and remains relevant in modern times, performing both decorative and sacred functions. Embroidery has the property of reflecting the peculiarities of the inner world of the individual and the culture of the community, demonstrating values and individualism. In the course of the actualization of the use of embroidery ornaments, the question of a modern technological approach emerges, the choice of materials for embroidery, which have evolved from natural to modern factory threads, is also important, as this important aspect directly affects embroidery technologies and changes classical approaches to pattern design. In the context of European integration and globalization, it is important to preserve and adapt Ukrainian embroidery to modern needs, justifying a method that allows integrating Ukrainian traditions into modern design solutions and defining a new fashion direction in the context of neoclassical Ukrainian traditions. The approach proposed by the authors to the analysis of regional traditions contained in embroidery patterns fully allows one to convey one's own national motifs by demonstrating the ornaments of vyshyvanka.
ФІЗИЧНІ ВЛАСТИВОСТІ ГІДРОГЕЛІВ ТА ПЛІВОК ПВС НА ОСНОВІ ВОДНОГО ЕКСТРАКТУ КРОПИВИ ДВОДОМНОЇ
Authors: ЛЯШОК ІРИНА , КРЮКОВА ОЛЕНА , ШВЕЦЬ ВЯЧЕСЛАВ , КИЧУЖИНЕЦЬ МАКСИМ , ГАЛАГАН ВІКТОРІЯ
Published: January 2025

The article considers the possibility of creating bilayer films and hydrogels from polyvinyl alcohol (PVA) with polysaccharides: potato starch (Kr) and carboxymethyl starch (KMK) based on an aqueous extract of nettle. The rheological properties of PVA, PVA/Cr and PVA/KMK compositions based on the aqueous extract of St. Nettle were studied, and it was established that the PVA solution based on the aqueous extract of St. Nettle and the composition of PVA/KMK solutions are characterized as pseudoplastic liquids, for which the viscosity decreases with increasing shear stresses. And the PVA/Kr composition based on the aqueous extract of St. Nettle belongs to dilatant liquids, that is, systems for which the viscosity increases with an increase in the rate of shear deformation.
It was found that the sorption curves of PVA films based on the aqueous extract of stinging nettle have a form characteristic of crystalline polymer materials, the maximum value of sorption of distilled water increases by 27% when starch is added, and by 420% when CMC is added. When starch is added to the film composition, the maximum value of sorption of physiological NaCl solution increases by 35%, the addition of CMC leads to an increase in this indicator by 294%. In general, PVA films based on the aqueous extract of stinging nettle swell less in physiological NaCl solution than in distilled water, by 32%, PVA/Cr – by 24%, and PVA/CMC by 208%.
Therefore, the addition of starch to PVA compositions based on an aqueous extract of stinging nettle increases the swelling of films in both distilled water and physiological NaCl solution by almost the same 1.03 times. And the addition of KMC to PVA compositions based on an aqueous extract of stinging nettle increases the swelling of films in distilled water by 1.45 times, and in physiological NaCl solution by 1.3 times.
 It was established that the addition of starch to the composition of PVA leads to an increase in the degree of swelling of hydrogels based on the aqueous extract of St. Nettle in distilled water and in physiological NaCl solution by 280% less than the addition of KMC. It was found that the addition of KMC to PVA based on nettle extract leads to a decrease in the rate of drying of hydrogels. Recommendations for the use of PVA hydrogels and films based on the aqueous extract of St. Nettle, taking into account the influence of starch and KMC on physical properties, are given.
ВИКОРИСТАННЯ ШКАРАЛУПИ ВОЛОСЬКИХ ГОРІХІВ В ЯКОСТІ ПАЛИВА
Authors: ЦУРКАН ОЛЕГ , СПІРІН АНАТОЛІЙ , РУТКЕВИЧ ВОЛОДИМИР , ДІДИК АНДРІЙ
Published: January 2025

При повній переробці волоських горіхів окрім основного продукту – ядра горіха, залишається в тому числі і його шкаралупа. Технологія переробки волоських горіхів передбачає наявність процесу сушіння який є найбільш енергозатратним для всієї технології. Найбільш розповсюджені в сільському господарстві сучасні конвективні сушарки витрачають 5,5 – 6,0 МДж/кг випаруваної вологи. В умовах сьогодення при значному дефіциті традиційних джерел енергії доцільно звернутись до альтернативних палив, одним з яких є шкаралупа волоського горіха. Вона має високу теплоту згоряння (21 МДж/кг) і низьку зольність.
Аналіз останніх досліджень і публікацій свідчить про те що проблема використання рослинних решток в якості палива розробляється вітчизняними та зарубіжними дослідниками. Основна увага приділена відходам основних культур що вирощуються в Україні: пшениця, кукурудза на зерно і соняшник. Використання відходів як палива вимагає специфічних умов організації процесу горіння, експлуатації паливоспалювальних установок і облаштування систем очищення продуктів згоряння.
Аналіз останніх досліджень показує що питання теорії та практики згоряння шкаралупи волоських горіхів залишається відкритим. Основна увага приділяється «традиційним» паливам із рослинних решток.
Метою досліджень є зменшення затрат енергії при переробці волоських горіхів шляхом розробки теоретичних та практичних заходів та засобів для використання шкаралупи горіхів в якості палива. З енергетичної точки зору  шкаралупа волоського горіха стоїть в одному ряду з традиційними паливами які використовують в тому числі і в сільському господарстві. Адже теплота згоряння паливних брикетів з волоського горіху становить близько 21МДж/кг, причому при дуже малій зольності (близько 1 %). Для порівняння: теплота згоряння умовного палива становить 29,35 МДж/кг, природного газу 33-38 МДж/м3, бурого вугілля в середньому 24 МДж/кг, деревини 10-12 МДж/кг.
ІНТЕГРАЦІЯ МОДЕЛЕЙ ПРОГНОЗУВАННЯ ДЛЯ ПІДВИЩЕННЯ ЕФЕКТИВНОСТІ МОНІТОРИНГУ ТРАНСПОРТНОГО ВПЛИВУ НА ДОВКІЛЛЯ
Authors: ГАЛАКТІОНОВ МИКОЛА , БРЕДУН ВІКТОР
Published: January 2025

Urban air pollution caused by vehicle emissions is becoming a growing problem, especially in industrially loaded cities such as Kryvyi Rih. Constant heavy traffic and the operation of vehicles that do not meet modern environmental standards significantly affect the quality of atmospheric air. Traditional methods of pollution control are often insufficient to respond in a timely manner to continuous changes in air quality, resulting in the introduction of restrictions only after critical levels of pollution have been reached. This approach is ineffective for long-term air quality management. The article considers the importance of implementing forecasting systems as an integral component of environmental monitoring. Forecasting systems make it possible to assess changes in atmospheric air quality in advance and to take measures in time to minimize the harmful effects of motor vehicles. Such systems are especially important in high-traffic areas where the accumulation of pollutants can quickly exceed safe levels. The implementation of such technologies will allow cities to manage traffic flows more effectively, reducing the intensity of traffic during periods when the risk of pollution is the highest. This research focuses on developing approaches for integrating forecasting models with real-time monitoring systems. Such integration allows for a more accurate picture of the impact of transport on the air environment and timely response to potential environmental threats. In addition, the results show that the management of traffic flows based on predictive models can significantly reduce emissions, especially in areas of the highest load, such as transport hubs and highways. The implementation of such systems provides the possibility of planning urban transport networks taking into account environmental factors, which in turn increases the comfort of life of residents and reduces the negative impact on the environment.
HR-ТЕХНОЛОГІЇ ЯК ЦИФРОВІ ТРАНСФОРМАЦІЇ КОМПАНІЙ У США, ЯПОНІЇ ТА ЄВРОПІ
Authors: ФІЛЬ Олег , СВАТЮК Оксана
Published: January 2025

Українські лідери підприємств, як і їхні західні колеги, стикаються з необхідністю адаптуватися до нових реалій та впроваджувати інноваційні HR-технології. Для цього автори пропонують ряд конкретних рекомендацій з досвіду різних країн. Описано міжнародний досвід і проблеми ефективного управління страховими компаніями у світі в умовах кризи пандемії, що є актуальним для багатьох компаній на ринку.Американські компанії є лідерами в інноваційних HR-технологіях, таких як штучний інтелект, машинне навчання та великі дані. Вони активно використовують ці технології для автоматизації рутинних завдань, аналізу даних та прийняття рішень на основі даних.Японські компанії відомі своєю увагою до розвитку людського капіталу та створення довгострокових відносин з працівниками. Вони поєднують традиційні підходи до управління персоналом із сучасними технологіями, такими як системи наставництва (менторства) та 360-градусна оцінка.Європейські компанії приділяють велику увагу захисту даних та конфіденційності співробітників. Вони активно впроваджують технології, які забезпечують безпеку персональних даних і довіру співробітників Європи.Досвід цифрової трансформації HR у США, Японії та Європі є цінним для українських підприємств. Вивчаючи ці кейси, українські компанії зможуть: виявити найкращі практики та адаптувати їх до своїх потреб; уникнути типових помилок при впровадженні нових технологій; прискорити процес цифрової трансформації HR.
PENGARUH SOLVABILITAS, LIKUIDITAS DAN GOOD CORPORATE GOVERNANCE TERHADAP AUDIT DELAY PADA PERUSAHAAN YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2021-2023
Authors: Meo Maria Yunita , Paramitalaksmi Ratri
Published: January 2025

Laporan keuangan merupakan alat penting bagi pemangku kepentingan dalam pengambilan keputusan. Keterlambatan penyampaian laporan keuangan dapat mengakibatkan keputusan yang salah dan menurunkan kepercayaan masyarakat terhadap perusahaan. Penelitian ini bertujuan untuk mengeksplorasi pengaruh solvabilitas, likuiditas, dan Good Corporate Governance (GCG) terhadap audit delay pada perusahaan yang terdaftar di Bursa Efek Indonesia selama periode 2021-2022. Metode analisis digunakan untuk mengidentifikasi hubungan antara variabel-variabel tersebut. Hasil penelitian menunjukkan bahwa solvabilitas dan likuiditas memiliki pengaruh positif signifikan terhadap audit delay, sementara GCG tidak menunjukkan pengaruh signifikan. Secara simultan, ketiga variabel tersebut berpengaruh terhadap audit delay. Temuan ini memberikan wawasan penting bagi perusahaan dalam mengelola proses pelaporan keuangan dan meminimalkan risiko penundaan audit, serta kontribusi teoritis dalam literatur mengenai audit delay.
Characterization and Optimization Techniques for the Extraction of Fibers from Ficus Thonningii
Authors: Shitahun Yohannes , Adane Simegn , Aferu Terefe , Tadesse Kalkidan , Fentahun Biruk , Debebe Endalkachew
Published: January 2025

The investigation of natural fibers as viable substitutes for synthetic materials has intensified due to environmental and financial considerations. It has been acknowledged that Ficus thonningii is a viable source of natural fibers due to its resistance and capabilities. The current study aimed to extract and characterize F. thonningii fibers from F. thonningii plant found in Ethiopia. The extraction methods used included water and chemical retting with sodium hydroxide. The extraction was optimized by DOE. Mechanical, physical, and chemical properties of the extracted fibers, such as tensile strength, elongation, fiber length and diameter, fiber fineness, moisture content, moisture regain, fiber’s cellulose, hemicellulose, lignin, and ash contents were characterized. Results showed that F. thonningii fibers have comparable fiber strength (39.65cN by chemical extraction and 37.83cN by water extraction), elongation (3.02% by water extraction and 2.6% by chemical extraction), fiber length (101.5mm by both methods), moisture content (10.35% by water extraction and 10.78% by chemical extraction), and moisture regain (11.02% by water extraction and 11.98% by chemical extraction) with jute, sisal, and flax. The chemical composition was found to be 52.35% of cellulose, 19.2% of hemicellulose, 17.2% of lignin, and 1.2% of ash for water extraction and 63.57% of cellulose, 16.1% of hemicellulose, 12.1% of lignin, and 0.83% of ash for chemical extraction. This proves that F. thonningii plant found in Ethiopia is a source of coarse fibers, thus, can be utilized for technical textiles application.
Actantial Paradigm of Narrative Structures in Techno-thriller and Visionary Fiction
Authors: Khan Ramsha , Khan Azka
Published: January 2025

This study examines the structural patterns of two radically distinct genres, namely techno-thriller and visionary fiction, by focusing on the actantial elements of fictional works. It seeks to clarify misconceptions about traditional literary analysis by comparing the novels Rumi's Daughter by Maufroy (2004) and Deception Point by Brown (2001). The actant theory, first introduced by Greimas (1971) and later amended by Hébert (2020), is employed to analyze the roles of characters, exploring both their similarities and differences within the internal narrative structure of the selected novels. The study investigates narratives’ universal “grammar” by focusing on three pairings of binary oppositions, that is, subject/object, sender/receiver, and helper/opponent. Despite the differences in theme, culture, characters, and genre, the study shows that the characters’ narrative structure and actantial function are the same, proving Greimas’ claim that the actantial theory applies to all narratives. This study contributes to the basic understanding of the fundamental patterns that connect human narratives, despite the apparent differences between the civilizations they belong to.
Writing Trauma: Poetics of Cultural Trauma and Memory in Anglophonic Kashmiri Literature
Authors: Ashraf Rabia , Akhtar Rizwan
Published: January 2025

This study concentrates on the Anglophonic literature produced in the region of Jammu and Kashmir. It explores its narratives through the lens of trauma theory, pertaining to the region’s history of forced conflict. After the Second World War, the relevance of trauma in literary studies has increased and texts have been characterized by an  archeology of traumatic consciousness. Also, the narratives act as vehicles for transmitting stories of suppressed and wounded consciousness. This research focuses upon Mirza Waheed’s (2011) novel The  Collaborator and Basharat Peer’s (2010) memoir Curfewed Night as the primary texts and investigates the art of writing trauma by exploring the narrative structures deployed by the authors. The objective is to find out as to how the very act of writing trauma is shaped by traumatic memories of a past rooted in the partition conflict, war, and prolonged violence. Furthermore, the study probes into how the fictional characters embody and express pain and anguish as part of their memories. The key focus remains on how both the works portray the (un)speakability of grief and the (in)comprehensibility of trauma drawing on some of the seminal contemporary theories of cultural trauma and memory studies. Using qualitative methodology and trauma theory as the theoretical framework, it is concluded that apart from presenting reality as horrific, gloomy, and glim, Kashmiri texts discuss how causalities create memories riddled with unspoken fears by bringing forth the intricacies of speechless terror and trauma. Thus, the study captures the narration’s struggle to represent evasive and suppressed memories and the challenges of trauma writing.
Mirative Status of the Urdu Discourse Marker to
Authors: Sharif Ahmad Naveed , Hussain Jabir
Published: January 2025

This study explicates the licensing conditions for the mirative behaviour of the Urdu discourse marker to, that is, how do declaratives become miratives in the presence of the discourse particle to? To explore the semantic contribution of this particle, the study uses Evans’ Lexical Concept and Cognitive Model (2009), since it combines linguistic and cognitive systems to account for a situated meaning. The study employs naturally occurring data, introspection, and Urdu Lughat to mitigate the limitations associated with an individual source when used in isolation. It finds that the discourse particle to contributes a non-propositional mirative meaning when it interacts with other lexical concepts undergoing the semantic compositional processes, namely selection, integration, and interpretation. The use of to and prosodic construction in declaratives remain in complementary distribution. The findings imply that both linguistic and non-linguistic factors account for form-meaning relation in Urdu language.
Exploring Spatiality in Selected Poems of Moniza Alvi: A Poetic Cartography of Displacement
Authors: Ahsan Rija , Anjum Nadia
Published: January 2025

This research aims to analyze the dynamics of space in Moniza Alvi’s seven poems from her collection The Country at my Shoulder (1993). It explores how spatial anxiety and dislocated geographical and cultural concerns become prominent in her poems through different spaces. This research mainly highlights the collision of two diverse cultures and value systems in Alvi’s poems to bring forth her transcultural quests, which display the influence of geographical perplexity on postmodern literature. The research employs the theoretical framework of spatiality primarily discussed by Gaston Bachelard, Henri Lefebvre and Benjamin N. Vis. First, architectural spaces, such as rooms and buildings, are discussed in the context of her native culture, as architectural trends of a nation are representative of its culture. Second, social and filial spaces are traced in the form of city space and social ties to unearth their influence on the poet’s existence. Third, diasporic spaces are analyzed through the contrast of oriental and occidental psyches to determine the poet’s vacillation between dual cultures. Fourth, geological and body spaces are interpreted through the metaphor of a displaced geography to highlight the angst of dislocation. These spaces are specifically explored in the light of the philosophies of different critics of space. This exploration shows that Alvi’s poetry proves to be a multi-spatial platform that is reflective of the general restlessness of the 21st century due to postmodern spatial crisis and the dilemma of migration.
Exploring Intentionality and Temporality in Alan Lightman’s Einstein’s Dreams: A Phenomenological Perspective
Authors: Malik Noureen Sagheer
Published: January 2025

This research examines Alan Lightman’s Einstein’s Dreams through the phenomenological framework introduced in Edmund Husserl’s book “On the Phenomenology of the Consciousness of Internal Time” which focuses on temporality and intentionality. Lightman’s novel, composed of imaginative vignettes, each depicting a unique conception of time, provides a fertile ground for phenomenological analysis. Employing Husserl’s notions of lived experience and consciousness, the current study explores how Lightman’s narratives extend beyond the scientific domain to probe the subjective human experience of time. The study argues that Einstein’s Dreams not only reflects Husserl’s ideas on temporality - the flow of time as experienced by consciousness - but also embodies his concept of intentionality, the idea that consciousness is always directed towards something. Through qualitative textual analysis, this study highlights how Lightman’s portrayal of various temporal dimensions aligns with Husserl’s emphasis on the individual’s perception of time, rather than an objective measurement. By intertwining scientific imagination with phenomenological philosophy, Lightman transcends the boundaries of traditional science fiction, inviting readers to engage with the deeper existential implications of time and consciousness. This research contributes to a subtle understanding of how literature can illustrate and expand phenomenological concepts, particularly in the intersection with theoretical physics.