bluuebunny/crossref_metadata_2025 huggingface dataset:
RESEARCH ON THE USE OF POSTGRESQL IN A HUMAN RE-IDENTIFICATION INFORMATION SYSTEM
Authors: Kvyetnyy Roman , Kyrylenko Oleksandr , Garmash Volodymyr
Published: December 2024

This paper investigates the application of the PostgreSQL database management system in the context of human re-identification systems based on computer vision technologies. Considering the growing need for efficient storage and processing of large-scale vector data obtained through deep neural networks, the issue of optimizing databases for fast and accurate matching of individuals' vector features arises. The study examines the specifics of storing high-dimensional vector representations in PostgreSQL using the pgvector extension, which provides efficient similarity search capabilities using metrics like cosine similarity and Euclidean distance. A detailed experimental analysis of PostgreSQL's performance was conducted during the execution of nearest neighbor search operations (k-NN search) based on vector features obtained from the open dataset Market-1501. The speed and accuracy of PostgreSQL were compared with other popular DBMSs such as MySQL and MongoDB, utilizing similar data storage and indexing methods. The research results demonstrate that PostgreSQL with the pgvector extension provides significantly better performance, achieving an average query execution time of 35 ms and a throughput of 285 queries per second, surpassing the metrics of MySQL and MongoDB. Moreover, the use of PostgreSQL contributes to increased accuracy in re-identification, as confirmed by higher mAP (mean Average Precision) values (78% compared to 72% in MySQL and 70% in MongoDB). Factors influencing system performance are discussed, including indexing efficiency, query optimization, and system resource utilization. The paper also explores the scalability of PostgreSQL for processing even larger volumes of data and its integration with other tools to enhance performance. The obtained results confirm the feasibility of using PostgreSQL in human re-identification systems, which can have practical significance for developing high-performance and scalable security and monitoring systems. Future research may focus on optimizing search algorithms and integrating advanced machine learning technologies to further improve system accuracy and speed
BUILDING AN ACCEPTANCE SUPPORT SYSTEM MEDICAL DECISIONS BASED ON HETEROGENEOUS ENSEMBLE CLASSIFIER
Authors: Povoroznyu Anatoly , Povoroznyuk Oksana , Filatova Anna
Published: December 2024

Based on the analysis of diagnostic methods used to make a diagnosis by a doctor in accordance with the requirements of evidence-based medicine, as well as methods of constructing diagnostic decision rules in medical decision-making support systems, two approaches to the formulation of a diagnostic conclusion are distinguished. The first is the traditional approach of medical practitioners based on the identification of disease symptoms and analysis of the structure of symptom complexes, taking into account the experience of clinicians in this subject field of medicine, which is covered in medical handbooks, and it can be considered an expert assessment of each disease. The second is a formalized approach based on the synthesis of a probabilistic classifier that is trained on a training sample. Since these approaches consider the same problem from different points of view, their joint use is promising. Implementation of different types of classifier models and aggregation of their results is possible when implementing a heterogeneous ensemble classifier. The goal of the study is the synthesis of a heterogeneous ensemble classifier that takes into accounts both the expert and probabilistic components of the diagnosis process. In the paper, a mathematical model of a heterogeneous ensemble classifier is developed and the choice of its components is substantiated. As a probabilistic component, widely used classification methods are selected: the method of comparison with a prototype, the method of K-nearest neighbors, and the method of potential functions. Formalized expert information on the structure of symptom complexes by presenting the symptom complexes of diseases with numerical intervals of values "below normal", "normal", "above normal" of linguistic variables. Considered options for taking into account expert assessments regarding the structure of symptom complexes in the ensemble classifier. The decision support system was designed and a comprehensive check of the developed system was carried out on real medical data, which confirmed the effectiveness of the system.
FILTERING ALGORITHMS FOR OPTICAL COHERENCE TOMOGRAPHY IMAGES
Authors: Scherbatyuk Artem , Tuzhanskyi Stanislav
Published: December 2024

The paper provides a comparative analysis of three image filtering algorithms used to improve the quality of optical coherence tomography (OCT): anisotropic diffusion, bilateral filter, and Lee filter. The task of the study was to determine which of the following filters is more suitable for filtering OCT images, which will contribute to more accurate diagnosis of diseases in ophthalmology. Diagnostic data obtained with OCT can be distorted due to the presence of noise, so the correct choice of filtering algorithm is an important step in the image processing process. Anisotropic diffusion is a filtering technique that reduces noise while preserving important image details such as structure boundaries and contours. A bilateral filter is a non-linear filter that takes into account both the spatial arrangement of pixels and their intensity. The Lee filter is an adaptive method that uses local statistical properties of pixels to reduce noise. It works well on images with a uniform texture, providing a high level of noise reduction. The mean square error (MSE) calculation was used to evaluate the effectiveness of the filtering algorithms. MATLAB software was used for image analysis, images with a size of 512x512 pixels are presented in black and white format. The results of the MSE calculations showed that the anisotropic diffusion has smaller values of root mean square error, which indicates its higher efficiency compared to other methods on the given set of images. Thus, the conducted research confirmed that the choice of the optimal filtering algorithm depends on specific tasks and a specific image. The presented filtering algorithms are useful for improving the quality of OCT images, which contributes to increasing the accuracy of ophthalmic diagnostics.
CONTROL AND MANAGEMENT OF DISTRIBUTED INTRUSION DETECTION SYSTEMS USING LOGS IN ADVERSE CONDITIONS
Authors: Boiko Viktor , Slatvinska Valeriia
Published: December 2024

This paper proposes an asynchronous system of control and management of the log verification and audit system, which is based on asynchronous procedures for sending "receipts" (push/pull) by nodes of different levels of the network infrastructure and maintains operability in conditions of partial loss of functionality of the network infrastructure. The problems of management and control of distributed intrusion detection systems (SIEM) in adverse conditions (blackouts, cyberattacks, etc.) are considered. Shown the role of SIEM in reducing the time interval between intrusion into a system and its malware infection and detection of the fact of intrusion. The problems of existing SIEMs are listed, the classification of intrusion detection methodologies is given, and the essential role played by system logs (logs) in detecting and eliminating cyber threats is indicated. The work describes various possibilities of control and verification of system logs: a system based on linked lists, systems based on hash trees (Merkle Tree and Verkle Tree). The task of creating a system that is insensitive to full or partial temporary disruption of the connectivity of the network infrastructure, which may occur as a result of adverse influences, is set. The deployment of proposed system, on the one hand, allows preserving and maintaining integrity of logs under conditions of adverse effects, on the other hand, due to asynchrony, it allows you to evenly distribute the load within the network infrastructure without overloading the information audit nodes with a large amount of calculations. The implementation and deployment of the system based on the proposed principles requires fewer resources compared to existing SIEM systems and can be implemented both independently and with integration into an already deployed SIEM, if any. The proposed measures will make it possible to significantly increase security, prompt response to incidents, and the ability to restore existing information networks.
DEVELOPMENT OF POWER ACTIVE FILTER CONTROL DEVICE ON ESP32 PLATFORM
Authors: Lebed Denys
Published: December 2024

This work deals with the development of a control device for an active filter based on an ESP32 microcontroller. The main goal of the development is the effective compensation of harmonic distortions in electrical networks that arise under the influence of non-linear loads. The paper describes in detail the circuits of voltage and current sensors used to monitor network parameters, as well as their integration with ESP32 for data collection. Voltage and current sensors play a key role in ensuring the accuracy of filter control. Their circuits include precision resistive dividers to measure voltage and Hall sensors to measure current. As a result of receiving signals from these sensors, an analog signal is generated, which is converted into a digital one using the built-in ESP32 ADC. Special attention is paid to the analysis of signal diagrams from sensors that demonstrate changes in electrical parameters in real time. This ensures quick response of the system to changes in the load and effective control of the active filter. ESP32 performs the generation of a PWM signal, which serves to control the inverter of the active harmonic filter. The work considers the methods of generating PWM signals that ensure the minimization of harmonic distortions in the network. The generation of PWM signals takes place using a 16-bit generator, which allows for high accuracy and smooth control of voltage and current with the help of an inverter. Features of setting the frequency and pulse width for adaptation to changing operating conditions of the active filter control device are also given. The algorithm for converting signals from sensors is based on high-speed reading of analog signals, their filtering and processing to form control actions. To ensure the operation of the power active filter control device, software code is used, which allows the system to simultaneously read data, generate a control signal and monitor network parameters. The results of this study can be used in industrial systems and household networks to improve the quality of electrical energy by actively compensating harmonic distortions.
SELECTION OF BALANCING METHODS FOR LOCAL POWER SYSTEMS WITH RENEWABLE ENERGY SOURCES
Authors: Lezhniuk Petro , Malogulko Yulia , Lastivka Victoriia
Published: December 2024

The analysis of power balancing issues in electric power systems related to the unstable energy generation by solar and wind power plants, which depends on natural conditions, was carried out in this work. Such variability is especially noticeable during sudden weather changes, when the performance of renewable energy sources (RES) can fluctuate significantly, affecting the stability of power supply. The research focuses on the issues of capacity reservation, which is key to the reliability of the power system, especially during peak consumption periods. The use of electrochemical storage devices, hydrogen installations, and biogas technologies for energy optimization and system stability enhancement is considered. Mathematical models based on the similarity theory method are used to evaluate the effectiveness of capacity reservation. These models allow assessing technologies based on such criteria as power, cost, operational expenses, and response speed to changes in energy production or consumption. The criterion method provides an accurate comparison of technologies, helping to select the most effective capacity reservation options according to the needs of the power system, considering technical and economic conditions. Models created based on this approach allow adapting decisions regarding technology implementation depending on system parameters. Special attention is paid to the centralized placement of technologies in local energy systems (LES), considering transmission losses, which helps reduce transmission costs and more efficiently use resources, especially in remote areas. Optimizing losses and maximizing the use of reserve capacities significantly improves the efficiency of power systems based on renewable energy sources. This is important for the sustainable development of the industry, especially considering the decarbonization of energy. The conclusions emphasize the significance of the criterion method for improving power system stability, cost optimization, and integration of renewable energy sources. This not only improves the reliability of the system but also reduces dependence on variable climatic factors. Effective reservation is a crucial factor in the sustainable development of modern energy, meeting the demands of growing urbanization and the demand for clean technologies.
THE ROLE OF ARTIFICIAL INTELLIGENCE IN MANAGING THE SAFETY AND EFFICIENCY OF NUCLEAR POWER
Authors: Zakharchenko Viktor , Netrebskyi Volodymyr , Taraniuk Yaroslav , Shevchuk Sergii
Published: December 2024

The author analyzes the key areas of application of artificial intelligence technologies in the energy sector. The main priorities for the application of modern technologies in energy supply systems were highlighted. We have also AI assistance with errors caused by human factors was studied. Separately, the possible use of artificial intelligence was considered application of artificial intelligence to assess the technical condition of a power transformer based on AI. The development of an AI-based serviceability index (SI) model is presented. The proposed method is aimed at simplifying, accelerating, and reducing errors. In the proposed approach, artificial intelligence evaluates the insulation system of power transformers based on oil quality, chromatographic dissolved gas analysis (DGA), and the condition of the paper insulation. The report also highlighted the challenges that complicating the rapid implementation of artificial intelligence.
MONITORING THE EFFICIENCY OF ACTIVITIES RELATED TO THE FORMATION OF SMART GRIDS BASED ON AN INTEGRATED QUALITY INDICATOR
Authors: Komar Viacheslav , Semeniuk Yurii , Pirhorets Serhii
Published: December 2024

The current level of electrification necessitates higher standards for electricity supply quality, highlighting the importance of the efficient organization, operation, and management of electricity systems. Addressing these challenges has become more complex with the increased integration of renewable energy sources (RES). This is particularly relevant for distribution power grids, which, due to their structural characteristics, are generally not adapted to accommodate fluctuating energy sources owing to insufficient network automation. This paper presents an approach based on an integral metric to evaluate the readiness of power grids to meet specific electricity supply requirements. The proposed metric is derived from an analysis of electricity supply quality within the context of accelerated RES development and power grid characteristics critical to quality performance. Such a metric is valuable for forming general strategies and solutions for grid development, particularly with respect to RES integration and the intellectualization of power systems. The integral indicator components are expressed as the probability that the operational mode aligns with an 'ideal' mode. This «Ideal» mode is determined using the least-impact principle and corresponds to a substitute network scheme based on the rscheme, thereby reducing subjectivity in assessments and subsequent decision-making.It is demonstrated that this approach to defining the integral indicator of power grid performance quality enables not only an assessment of current grid readiness but also consideration of specific consumer preferences in design decisions. The methodology outlined here details a progression from relative performance evaluations of grid components to cost assessments, ultimately allowing for technical and economic analyses. This approach facilitates targeted planning for measures aimed at improving grid performance quality and the reliability of power supply to consumers.
AUTOMATION OF GEOLOCATION OF TEXTUAL INFORMATION FOR CONTROLLING THE EFFECTIVENESS OF RIVER BASIN MANAGEMENT MEASURES
Authors: Bondalietov Kostiyantyn , Mokin Vitalii
Published: December 2024

The work is devoted to the problem of controlling the effectiveness of the implementation of measures from the River Basin Management Plan (RBMP) and finding approaches to their optimization. The technology of automated collection and processing of textual information from alternative sources, in particular the websites of environmental institutions and social networks regarding the state of water resources after the application of those measures, is proposed. Web scraping methods and specialized libraries BeautifulSoup and Newspaper4k are used to collect text information from search results and selected information sources. To automate the geolocation of collected information to specific bodies of water, the method developed by the authors of comparing keywords with words from the description of bodies of water is used, and the selection of keywords is carried out using another author's method. In order to spread positive experience or problems related to the results of the application of measures, the text information augmentation method developed on the basis of the SpaCy library is used from one body of water and basins to others. Therefore, the proposed technology allows to increase the effectiveness of controlling the effectiveness and analysis of analogues regarding the implementation of RBMP measures in various river basins, thanks to the automated collection and analysis of a large amount of text data from publicly available alternative (including unofficial) sources of information. The proposed approach makes it possible to more effectively compare and recommend specific PURB measures to specific, similar, bodies of water, which improves the management capabilities of river basins. Thus, the proposed approach increases the effectiveness of decision-making and scientific justification for the sustainable use of water resources, improvement of the ecological state of waters, preservation and restoration of biodiversity and ecosystems of the river basin..
DEVELOPMENT OF AN EFFICIENT METHOD OF OBJECTS IDENTIFYING IN CONTROL SYSTEMS
Authors: Bykov Mykola
Published: December 2024

The paper presents the theoretical justification and software for an effective method of data identification in intelligent control systems, which is based on the use of the stages of clustering and classification of objects represented by their parametric description. The author proposed a method of data clustering with fixation of cluster boundary points based on the principle of finding their surface tension. The application of this method of cluster analysis allows to increase the efficiency of identification of objects in control systems using the SVM type classifier. The SVM (Support Vector Machine) type classifier is currently the most advanced and, due to the use of generalized decision functions, is able to operate with both linear and non-linearly distributed images of objects in the parameter space. Today, a significant number of cluster analysis methods and algorithms are known. They can be divided into classical, based on the general algorithm of Fu K.S., and the latest, based on taking into account the nature and structure of data and the purpose of their use. Examples of such methods include: k-means, density-based (DBSCAN), Mean-Shift, using Gaussian mixture models (GMM), methods of hierarchical agglomerative clustering (HAC) . Their common drawback is that they form clusters of points in the parameter space, but do not fix their boundary points. The last characteristic (the presence of marked cluster boundary points) is very useful when building classifiers that implement the task of object identification. In this paper, the author proposed and theoretically substantiated the method of clustering with the definition of surface points by analogy with the physical principle of surface tension of a liquid. The work developed an algorithm for the implementation of this method, as well as software in the Python language in the form of the ClusterBorderFinder application. The author's certificate was obtained for the developed program.
TRENDS IN THE USE OF ARTIFICIAL INTELLIGENCE IN ENDOSCOPY
Authors: Poudanien Yurii , Kozhemiako Andriy
Published: December 2024

This study provides a comprehensive overview of current trends in the application of artificial intelligence (AI) in endoscopic examinations of the gastrointestinal tract (GIT). AI significantly enhances medical diagnostic capabilities, particularly in detecting early signs of oncological and other diseases of the GIT. The analysis highlights the advantages and disadvantages of AI as an auxiliary tool for gastroenterologists, capable of improving examination 4 accuracy and reducing the risk of missing pathologies that are difficult to recognize during the procedure. Particular attention is given to the use of convolutional neural networks (CNN), which demonstrate significant results in image analysis and enhancement. The research discusses two primary approaches in endoscopy: classical and capsule endoscopy. Capsule endoscopy allows for thorough video analysis and is an effective tool for detecting lesions in hard-to-reach areas of the GIT, although its efficacy may depend on the quality of video, type of endoscope, camera, and algorithms used for data processing. Classical endoscopy, on the other hand, remains a widely used method that provides the opportunity for direct examination of the mucosal surface and allows specialists to utilize various image enhancement techniques to identify subtle changes. Studies indicate that the application of AI in classical endoscopy can achieve accuracy rates of up to 98% in identifying potentially hazardous areas, including the specific differentiation of lesion depths. Additionally, this work focuses on the challenges facing AI in endoscopy, particularly image artifacts that may negatively impact analysis results, as well as ethical considerations and data privacy compliance in medical data handling. Despite existing challenges, AI demonstrates significant potential as an assistant for both novice and experienced specialists, enabling the minimization of error risks and improving early disease detection. Overall, the findings indicate that artificial intelligence holds great promise in medicine and can significantly enhance the quality of endoscopic procedures, especially for early-stage diagnosis.
APPLICATION OF A VIRTUAL ASSISTANT IN AN INTELLIGENT SYSTEM FOR MARKING AND ACCOUNTING OF MATERIAL RESOURCES
Authors: Starzhinskii Valeriy , Bisikalo Oleh
Published: December 2024

The article considers an example of implementing a virtual assistant into an intelligent system for marking and accounting of material resources. The main goal of the development is to simplify the information management process and increase the efficiency of accounting operations through automation. To integrate the virtual assistant, the Telegram Bot API was used, which provides quick and convenient access to information through a popular messaging platform. Particular attention was paid to the development of the relational database structure, which serves as the basis for the functioning of the system. The database tables are created based on input data and optimized for effective interaction with the bot, which allows users to quickly obtain the necessary information and update data about resources. The system has the potential for application in various areas where it is important to ensure accurate control over material resources
USE OF ARTIFICIAL INTELLIGENCE IN AUTOMATED INTERIOR DESIGN TASKS
Authors: Kovaliuk Dmytro , Kovaliuk Oleh , Malitskyi Vadym
Published: December 2024

The paper analyses current trends in interior design. It is shown that the most promising way to take into account the personalized requirements of customers and the variety of interior objects is the development of automated systems. This will allow to increase work efficiency by reducing the burden on designers, reducing task completion time, and allowing to make changes to projects more quickly. For the operation of such automated system, it is necessary to develop appropriate computer-aided interior design tools and human-machine interface software for inputting data and saving results. Based on the 3D-FRONT dataset, the ATISS neural network was configured for the task of automated design of kitchens and living rooms, taking into account the style of the rooms and the number of things. A web application for interaction with the user has been developed, which consists of a server part on FastAPI and a front-end part on Gradio. The user can upload photos of rooms to generate interiors and get a 3D model of the room as a result.
INCREASE THE SECURITY OF QR CODES IN MOBILE APPLICATIONS THROUGH AI PROTECTION AGAINST FRAUD AND PHISHING
Authors: Serediuk Hlib , Garmash Volodymyr
Published: December 2024

QR codes have become an important tool in modern mobile applications, allowing users to instantly access various information, make payments, interact with advertising campaigns, and use social networks. Such popularity of QR codes contributes to their rapid spread, but at the same time increases the risk of fraud and phishing attacks. Dangerous QR codes can contain links to fake web pages created by attackers to collect users' personal data or to redirect them to malicious resources that threaten data security and user privacy. This paper focuses on the study of methods to improve the security of QR codes in mobile applications using modern artificial intelligence (AI) algorithms that can detect potentially malicious QR codes and protect user data. The proposed approach involves the use of several AI tools, such as recurrent neural networks (RNNs) for analyzing the structure of URLs, classification algorithms for verifying the legitimacy of domains, and autoencoders for detecting anomalies that may indicate malicious intent. The developed system allows timely detection and blocking of suspicious QR codes, preventing possible attacks on user privacy and misuse of their data. Additionally, the study emphasizes the importance of the data collection and preparation stage for training AI models. Since the quality of the results depends on the completeness and quality of the training data, considerable attention is paid to the development of optimal methods for collecting and filtering information to ensure the effectiveness of detecting malicious elements in QR codes. The use of artificial intelligence to ensure the security of QR codes is a promising area that allows mobile application developers to integrate modern technologies to protect users from fraud and phishing attacks. This approach contributes to the creation of a safer digital environment and increases consumer confidence in mobile technologies, enhancing the overall security of using QR codes in everyday life
On the prospects of using sapropel solutions in drilling and repairing oil and gas wells
Authors: Leontiev D. S. , Semenenko A. F.
Published: December 2024

Western Siberia, in addition to its significant oil and gas reserves, also has huge resources of sapropel and peat, which are estimated at 40 % of the world's total. In world practice, there is a positive experience with using drilling and plugging fluids that incorporate sapropel additives in well construction.

The aim of this article is to investigate the impact of sapropel on the properties of drilling and plugging fluids.

To achieve this goal, we conducted laboratory studies using experimental methods to examine the effects of sapropel on the properties of drilling and plugging fluids. Our results indicate that sapropel can serve various roles in drilling fluids. These roles are weighting agent, thickener, corrosion inhibitor, biocide, clay stabilizer, and lubricating additive. We calculated the density of the developed sapropel drilling fluids, plastic viscosity, and fluid loss. Also, we assessed the prospects for using sapropel in production.

The authors believe that the research of sapropels in drilling and well repair in Western Siberia has been studied extremely poorly. This is the reason for the need for further exploration in this area. Based on the the scientific works reviewed and laboratory research, we have developed an effective method for constructing wells under abnormally low reservoir pressure. This method should help to optimize drilling technology in Western Siberia. This is the importance of the practical significance of our article.
Analytical and numerical solutions to the problem of the influence of pipes for receipt and distribution on the stress-strain state of the tank wall
Authors: Chepur P. V. , Tarasenko A. A. , Ivanov V. A.
Published: December 2024

The article considers the problem of determining the stress-strain state of the tank wall in the area where it connects with receiving and dispensing pipes (PRP). One of the significant factors influencing the overall stress-strain state of the tank wall, which is a thin shell according to fundamental laws of structural mechanics, is the presence or absence of settlement of the bases and foundations of the structural elements of the tank.

The article uses both classical structural mechanics methods, and existing analytical solutions. In addition to applying numerical methods, particularly the finite element method (FEM), implemented through the ANSYS software package The developed numerical model of the RVSP-20000 tank using the finite element method in ANSYS PC allowed to determine the displacements, deformations, and stresses in the structures in the junction area of the receiving and dispensing pipe and the RVSP tank wall. The numerical calculations revealed. As the numerical calculation in this article using the FEM complex has shown, the PRP, which has a connection with the reservoir at the level of maximum radial displacements of the wall from the hydrostatic pressure of the stored liquid, creates a significantly altered and potentially hazardous stress-strain state in the contact zone. This highlights the necessity of monitoring potential incompatible deformations in the foundations of both the PRP and the reservoir itself, and, if needed, implementing appropriate engineering measures.
Influence of point defects on intergranular fracture of steel
Authors: Pakharukov Yu. V. , Chekhunova A. M. , Morev A. V.
Published: December 2024

At present, it has been established that the ageing process of pipe steel is multistage. The first stage is characterized by the release of carbon atoms from the metal grains. The second stage is determined by the removal of inter-nodal atoms to the grain boundaries. This removal mechanism is related to the diffusion of carbon through the inter-domain space, facilitated by point defects such as vacancies. The most optimistic estimates give an unrealistically long time of the ageing process of steel. Thus the diffusion mechanism remains unclear.

The aim of this study is to construct a mechanism that would adequately describes this phenomenon. The authors believe such a mechanism should be related to point defects (vacancies). The leading method used in this research is theoretical analysis, which has led to the proposal of an effective way of influence of point defects in intergranular corrosion failure of steel is proposed.Under conditions of uphill diffusion in the linear approximation, mass transfer develops slowly and cannot enrich the adjacent grain boundary layers with impurities. The presence of defects makes the diffusion nonlinear.This study considers thermodefects generated by a temperature gradient. Based on changes in the magnetic properties of the samples, conclusions about the formation of the structure with the participation of carbon impurities displaced in the process of hydrogen introduction were made.

The results of this study can be used in the development of methods of increase of service life of pipe steels.
Results of exploration and evaluation of 4D effects based on repeated 3D seismic survey in aquatorial part of gas and condensate field
Authors: Kuznetsov V. I.
Published: December 2024

Seismic monitoring (4D seismic survey) of developed oil fields is a new direction in seismic survey. It is designed to solve the main task of field development – maintaining production rates while enhancing the oil recovery factor. Seismic monitoring of reservoir systems is series of 3D seismic surveys, spaced in time in order to receive the dynamic image of processes within the reservoir.

This article focuses on this promising direction and based on a real practical example. In 2008, 3D seismic surveys were conducted in aquatorial part of oil and gas condensate field, using the standard methodologies available then. This data formed the basis for the geological and hydrodynamic models of the field. Today, this field is in the stage of deep development of reserves. To assess, forecast, and involvement in development of new promising reservoirs in deeper intervals, a repeated 3D survey with improved observation system parameters was carried out in 2017.

As a result, two sets of data were collected for the same area, nine years apart. This created the prerequisite for evaluating 4D effects on the reservoirs that had been in operation throughout this period. To isolate the expected effects, 2D seismic-geological modeling was performed, and the seismic data were processed using a unified processing schedule. This article presents the results of data processing and analysis. The potential of using repeated 3D seismic surveys in aquatory for field development monitoring is demonstrated.
Groundwater hydrogeochemical features in interpermafrost taliks on the example of the field in the Republic of Sakha (Yakutia)
Authors: Shulgina A. A. , Beshencev V. A.
Published: December 2024

The hydrogeochemical characterization of groundwater is a crucial aspect of studying the spatial and temporal variations in groundwater resources, which is crucial for water resource utilization and environmental protection. This article presents the hydrogeochemical profile of interpermafrost groundwater of the Middle-Upper Cambrian horizon local aquifer, based on a case study from a deposit in the Sakha Republic (Yakutia). Also, this study analyzes the impact of both natural and anthropogenic factors on the chemical composition of the groundwater
Hydrogeological conditions of the Megionsky oil field
Authors: Berdova D. V. , Abdrashitova R. N. , Sal'nikova Yu. I. , Kovyatkina L. An. , Semyonova T. V. , Beshentsev V. A. , Poluyanov M G.
Published: December 2024

The aim of this study is to provide a comprehensive description of the underground hydrosphere of the Megionsky oil field. The field is located within the well-studied West Siberian megabasin. According to V. M. Matushevich's classification (1986), the stratigraphy of the Megionsky field is divided into three overlapping hydrogeological basins (Cenozoic, Mesozoic, and Paleozoic). The results of the analysis of the variation in water mineralization, formation pressures, and geothermal gradients with depth have justified the classification of the Megion oil field as a water-bearing system of the elision-type geodynamic origin. The aquifers and water-bearing complexes in the study area extensively utilized for drinking, domestic, and industrial water supply. Additionally, the Aptian-Albian-Cenomanian hydrogeological complex of the Mesozoic basin is also targeted for the disposal of excess associated water. These factors indicate a significant anthropogenic impact on hydrogeological systems. Understanding the hydrogeological features of the underground hydrosphere provides a foundation for designing measures to protect fresh and mineralized groundwater from contamination and depletion.
Displacement of Vulnerable Households under Climate-related Shocks in 2022
Authors: Hashmat Fariya , Bradley Tony , Nawaz Ahmad , Ghalib Asad
Published: January 2025

Against the backdrop of the recent 2022 floods in Pakistan, this article investigates the resilient capacity of 121 vulnerable flood-affected households in the Matiari District. It examines the role of their personal and societal capacities in preventing displacement, and it introduces a new conceptual model related to social capital theory. Based on this model, it empirically examines the situation of these households through a survey based on the Disaster Adaptation and Resilience Scale. The findings suggest that households with relatively high levels of stored capacities are less likely to be relocated and thus more likely to escape displacement. However, a few households with higher capital (gatekeeper households) did choose relocation, indicating a strategic response to mitigate their vulnerability. These findings outline policy options for mobilizing community resources to strengthen household resilience through the intervention of gatekeeper households so as to reduce vulnerabilities.
Addendum
Authors: Cadman Tim , Schlagloth Rolf , Santamaria Flavia , Morgan Ed , Clode Danielle , Cadman Sean
Published: January 2025

Since the publication of the article ‘Koalas, Climate, Conservation, and the Community: A Case Study of the Proposed Great Koala National Park, New South Wales, Australia’ in June 2023, the Government of New South Wales has continued to permit logging operations within the footprint of the proposed park on the state's Mid North Coast. Conflicts between forest industry advocates and the community epitomise tensions around the socioeconomic and sociocultural dimensions of society.
Re/Visiting
Authors: Takiguchi Ken , Minarti Helly
Published: January 2025

In the recent years, Singapore, which once dubbed “a cultural desert,” has produced performance curators who took important positions in the region. This essay explores what were behind such developments.

Since the late 1990s, curation, especially performance curation, was recognized as the key to turn the disadvantage of Singapore into its advantage by both artists and the government. Singapore's cultural rootlessness was reframed as its openness to any cultures, and the methodology to achieve it was concretized by theatre practitioner Keng Sen Ong through his curatorial projects. Ong developed the model of New Asia, a new reality for an urbanizing Asia where dynamic interaction between the traditional and modern, specificity and universality takes place.

The government of Singapore adopted Ong's vision of New Asia as the foundation of its cultural policy in the early 2000s. It was advocated that the ideal citizens in the new millennium should be attuned to his Asian roots and at the same time connected to the global market, and the artists with an ability of curating cultures were considered the role model of the new Singaporeans. Although the cooperation between the artists and the government emerged, their relationship is not straightforward. The ownership of the methodology of curation is still being contested between them.
Ethno-Aesthetics (Excerpt)
Authors: Arke Pia
Published: January 2025

So, Western appropriation and marginalization of the alien is constantly at work. You may want to stress that postcolonialism is an intellectual invention combining postmodernism and anti-colonialism in a way that conceals the continuation of colonialism by other forms of suppression and exploitation of the Third World. However, this is not an insight that in itself will transcend the regime of Western intellectualism from which it has sprung.
THEORETICAL APPROACHES TO UNDERSTANDING THE ESSENCE OF ENSURING THE ECONOMIC SECURITY OF AGRICULTURAL FIRMS
Authors:   ВНЗ "Університет економіки та права "КРОК", Генчевська Вікторія
Published: January 2025

The article analyzes the definitions and essence of the categories "economic security of the enterprise" and "ensuring the economic security of the enterprise" proposed in the scientific literature. The author's vision of interpreting the economic security of the enterprise and ensuring the economic security of the enterprise is proposed and substantiated. The advantages and disadvantages of approaches to defining the concepts of "economic security of the enterprise" and "ensuring the economic security of the enterprise" are determined. Functional components in the process of ensuring the economic security of agro-firms, namely financial, personnel, technical-technological, informational, power, resource, political-legal, market and interface, are considered, and their importance is substantiated. The main target orientations of agricultural firms in the process of ensuring economic security have been determined. The author's vision of the interpretation of the economic security of an agro-firm and ensuring the economic security of an agro-firm is proposed and substantiated.
Morphological characterization and DNA barcoding of farmers’ varieties of rice (Oryza sativa L.) of central India
Authors: Kujur M. J. , Koutu G. K. , Singh Yogendra , Singh S. K.
Published: January 2025

Assessment of variety distinctness is important for the registration and protection of traditional rice landraces. The present study was conducted to develop a procedure for the assessment of genetic diversity and relatedness among farmers’ varieties of rice collected from tribal farmers of Madhya Pradesh. To distinguish and characterize the 100 rice genotypes, 22 SSR markers were applied, which detected a total of 67 polymorphic alleles. The results suggested that the primer RM144, followed by RM263, RM16, RM341, RM122, RM11 and RM234, maybe the best markers for identification and estimating diversity. The polymorphic information content (PIC) values ranged from 0.02 (RM8 and RM510) to 0.617 (RM144), with an average of 0.255. The allelic richness per locus varied from 2 (about 10) to 6 (RM144), with an average of 3.05 alleles per locus. The major allele frequency per locus varied from 45% (RM341 and RM144) to 99% (RM8 and RM510), with an average of 80.7%. The pairwise genetic dissimilarity indices revealed the highest genetic dissimilarity of 72.7% between Khuddi and Pasai Dhan and the lowest genetic dissimilarity of 3.4% was recorded between Bhata makadas and Ranikajal. Colored DNA fingerprint was produced by 22 SSR markers, which can identify the 100 farmers’ varieties of rice under study
Heterotic grouping methods reveal differential breeding efficiencies and season-specific categorization of inbreds in tropical maize (Zea mays L.)
Authors: Bhat Jayant S. , Kumar C.S. Kantha , Mukri Ganapati , Neelam Sunil , Naidu G.K.
Published: January 2025

The selection of diverse parents is a prerequisite for the exploitation of grain yield heterosis and is a real challenge to maize breeders. Heterotic grouping assists the breeder in selecting such diverse parents, which reduces the number of crosses to be made by avoiding intra-group crosses. An investigation was carried out to evaluate 54 inbreds along with two testers (LM 13 and LM14) and 108 hybrids derived using two testers with hybrid checks during the rainy and post-rainy seasons of 2019. Heterotic grouping based on three biometrical methods, viz., Specific Combining Ability combined with line Pedigree and hybrid Yield information (SCA-PY), Heterotic groups Specific and General Combining Ability (HSGCA), and Heterotic grouping by GCA of Multiple Traits (HGCAMT (HGCAMT) was inconsistent between the seasons and showed similar but not identical trends within a season. The HSGCA method could classify all the inbreds studied in both seasons. The SCA-PY and HGCAMT methods could classify 49 and 31 inbreds, respectively in the rainy season and 43 and 40 inbreds, respectively, in the post-rainy season. Only 10 inbreds were grouped identically in both seasons by all three methods and 15 inbreds were assigned to different groups between the seasons by all three methods. Besides, 44 lines (81.5%) were inconsistently grouped by at least one of the methods between the seasons, implying the season-specific response by the hybrids. The SCA-PY method was 2.2 and 6.2% more efficient than HSGCA and 10 and 18.1% more efficient than HGCAMT during rainy and post-rainy seasons, respectively. Thus, the results of the study revealed differential breeding efficiencies of grouping methods and suggested to have season-specific heterotic grouping in maize.
Discerning of Ahu rice (Oryza sativa L) landraces of Assam for Phosphorus deficiency tolerance using molecular and morphological approaches
Authors: Touthang Letngam , Sarma Debojit , Sarma RN , Baruah Akhil , Kumar Amit , Singh Binay Kumar , Philanim WS , Jaiswal Sandeep , Kaur Simardeep
Published: January 2025

A set of thirty two Ahu rice landraces were analyzed for identification of P-efficient genotypes. Based on molecular data of 7 Pup1 markers, the genotypes were grouped into two major clusters. Out of the 32 genotypes, 13 genotypes having consistent amplification of the entire 7 Pup1 markers and grouped in same subcluster with Kasalath were identified as Pup1 positive group. Field evaluation was conducted in three different levels of P (0, 20 and 40KgP2O5/ha). Pool mean analysis showed high significant genotypic variations (P≤0.01 or 0.05) with G X E interaction for various yield traits, P-uptake and use efficiency. Heatmap quantitative clustering group the genotypes into 4 major clusters indicating wide variation in response to differential P- levels environment. Analysis of genetic variability revealed moderate to high PCV, GCV, heritability and GAM for various critical yield contributing traits. The PCA analysis extracted 4 principal components in which the first two components accounted for 71.50 % of the total variance. Pearson’s correlation analysis revealed significant positive association of grain yield with various yield parameters, P-uptake and use efficiency. While traits like sterility percent, plant height and days to flowering exhibits negative correlation with grain yield. Path co-efficient analysis using yield per plant as resultant dependent variable revealed direct positive effects by 11 traits with negligible residual effect of (0.0077). The present inquest revealed that genotypes with Pup1 gene have lesser percent yield reduction than Pup1 devoid genotypes. However, landraces like Gopinath with devoid Pup1 gene exhibit at par yield potential with Pup1 positive genotypes. This indicates the probable presence of unidentified P-deficiency tolerance locus among the landraces. Landraces like Kolong, Ikhojoi, Koimurali and Sadakara  with Pup1 positive were identified as promising in P-use efficiency.