Contemporary problems of intelligent systems

This article discusses the digitization of the scientific heritage of the Institute of Physics and Technology, focusing on its historically significant discoveries and developments. It explores the opportunities for visualizing scientific content and creating interactive educational materials using modem digital technologies. The study also provides practical recommendations for incorporating such digital content into educational platforms and curricula.

The article examines the role of digital technologies and artificial intelligence in the modem world, especially in the context of their impact on the global economy. Theoretical aspects of the use of artificial intelligence in science, education and industry are discussed, as well as practical examples of successful implementation of digital technologies in economic processes.

This article discusses methods for automating communication between healthcare workers and patients. An integrated communication platform is proposed, outlining its key advantages and the mathematical modeling basis.

This article covers the basic concepts of the Python programming language in a simple and understandable way. The article explains the capabilities, syntax, and practical uses of the Python language for new users with consistent and clear examples. The article also provides information about Python’s "pythonic" - that is, its unique and recommended writing style. The material is intended for students, students, and independent learners who are just starting out in programming.

This article discusses methods of organizing online classes aimed at developing students’ language skills. It reveals the advantages of using online platforms for learning a language and the methodology used in such classes.

This article examines the role and importance of artificial intelligence (Al) technologies in the digitization process of archival documents in Uzbekistan. Digitizing archival records ensures their preservation, facilitates their processing, and enhances public accessibility. The article provides an overview of the information systems introduced by the “Uzarchiv” Agency and explores how Al technologies are being applied within these systems. It also presents a comparative analysis of advanced international practices in countries such as the United States, the United Kingdom, South Korea, China, and other European nations, focusing on legal frameworks, digital infrastructure, and the integration of Al in archival management. The article concludes with practical recommendations for the development of the archival digitization system in Uzbekistan.

In today’s interconnected digital landscape, ensuring timely and secure dissemination of information about local events and incidents is critical for fostering community engagement. This article presents the development of an Android-based mobile application designed to provide real-time updates on local events while incorporating robust security measures such as data encryption, user authentication, and secure database management. Built using Android Studio and Firebase, the application offers features like event listing, real-time chat, and push notifications, all tailored to the cultural context of Uzbekistan.

The article examines various aspects of shaping students' creative thinking using digital technology. Tools, functional tasks used in the educational process are presented.

This article discusses the increasing role of Artificial Intelligence (Al) in English language education, highlighting its benefits and potential drawbacks. Three main purposes of Al in education have been outlined. Moreover, practical examples such as ChatGPT, Mentimeter, Gencraft, and Aspose Grade calculator are used to illustrate how Al is transforming teaching and learning processes. While acknowledging the advantages of Al in providing personalized learning, creating engaging materials, and automating assessment, the text also emphasizes the importance of critical thinking, teacher guidance, and responsible Al use. The conclusion stresses that Al is no longer a futuristic tool but a present-day resource, and educators must equip students to use it wisely and ethically.

The article defines the definition of students’ programming culture, its structure and assessment methods. The proposed approach is based on ABC abilities, as well as programming methods for the level of sensor proficiency.

This article is devoted to the importance of financial analysis and classification of financial indicators. The main goal of financial analysis is to improve the efficiency of business entities, assess the financial position and help make key decisions for its future. The article considers various objects and indicators of financial analysis, in particular liquidity, profitability, financial stability, efficient use of assets and debt ratios.

This article discusses the implementation of digital transformation to improve the effectiveness of education in higher education institutions and modernize educational processes. It also explores the opportunities for optimizing educational resources, effectively managing the working processes of students and teachers, and enhancing the quality of education through the introduction of digital technologies. The article presents measures and recommendations aimed at improving the educational process through the adoption of these digital tools.

This article examines the impact of digital technologies and artificial intelligence on logistics between Russia, China and Uzbekistan. The theoretical and practical aspects of Al application in logistics systems are described, as well as the possibilities of optimizing processes, increasing efficiency and reducing costs are analyzed. The strategic importance of logistics for the development of the economics of these countries in the context of globalization is emphasized.

This study analyzes the main image databases used in the fields of medicine, geography, agriculture, and biometric technologies. In particular, it reviews databases such as LIDC-IDRI, OASIS, Landsat, Sentinel-2, Google Earth Engine, PlantVillage, UAV-based crop monitoring datasets, LFW, and CASIA-WebFace. The research and developments carried out using these databases are also examined.

This paper investigates the impact of interpolation methods applied to multispectral images in pansharpening techniques aimed at enhancing spatial resolution. Specifically, interpolation methods such as nearest neighbor, bilinear, bicubic, and Lanczos were employed within the IHS, Brovey, PCA, Gram-Schmidt, and BDSD pansharpening approaches. These methods were compared in terms of their ability to preserve spatial details and reduce spectral distortions. Experimental evaluations were conducted using image quality assessment metrics including ERGAS, SAM, SS1M, and QAVE. The results indicate that bicubic and Lanczos interpolation methods provided the best performance in improving image quality.

The concept of developing an automated system for managing the trajectories of oil and gas wells through the use of modem information technologies is examined. A three-level algorithmic approach is proposed for making control decisions based on a predictive model of drilling equipment movement. An approach to constructing a multi-mode predictive model of well trajectory is presented, which serves as the mathematical foundation of an information-analytical subsystem aimed at solving real-time trajectory management tasks.

The article develops a mathematical model describing the processes of nonlinear filtration of groundwater in multilayer heterogeneous porous media that affect the flow of groundwater and the transport of pollutants.

This paper considers unsteady groundwater flow in a system of three aquifers. The hydrogeological structure consists of a highly permeable main aquifer, a poorly permeable interlayer, and a capping layer. The calculations take into account infiltration, evaporation, vertical and horizontal drainage, and interaction with underlying aquifers through the intermediate layer. Finite-difference approximation of differential equations is used to solve the problem.

The article analyzes the system of handling citizens’ appeals in our country, the processes of their reception and consideration, as well as the role of modern information technologies, particularly the Virtual Reception and the “Murojaatlar” portal, in these processes. It discusses the implementation of automated systems aimed at ensuring citizens’ rights, enhancing transparency, and reducing human involvement. The article highlights the significance of e-government platforms in improving communication between the state and citizens.

The paper presents a comparative analysis of machine learning algorithms applied for the early diagnosis of oncological diseases. The paper examines algorithms such as Random Forest, XGBoost, AdaBoost, and others, tested on various clinical tasks including cervical, lung, and skin cancer. Special attention is given to ensemble methods, which demonstrated the highest accuracy, particularly the Random Forest algorithm. The study emphasizes the versatility of the methods, their adaptability to heterogeneous medical data, and their potential for developing intelligent clinical decision support systems.

With the help of modem technologies and big data technologies, it is also becoming difficult to implement large volumes of texts in the Uzbek language. Training language models from large corpora, extracting meaningful information from real-time chats, semantic indexing of texts and creating search engines are all now implemented through the integration of platforms such as Hadoop, Spark, NoSQL, Kafka and Elasticsearch.

The content of information models as the basis for organizing information resources is revealed. The structure of the information model is described (a set of parameters, relationships between parameters, rules for construction, modification and use), as well as a number of properties of the information model, including the multidimensionality of objects, processes and phenomena, the complexity of its structure and the function of describing the presence of simple information units.

This work is dedicated to exploring the application of machine learning (ML) in transforming business processes within the digital economy. The study examines the potential of ML algorithms for automating management, forecasting key performance indicators (KPIs), and optimizing resource allocation. The article provides a detailed overview of theoretical foundations, the methodology for developing software solutions, and the results of experiments conducted on real-world data from logistics and e-commerce. Examples of using linear regression, random forest, gradient boosting, and neural networks are presented, demonstrating their effectiveness in enhancing productivity and reducing costs. The work emphasizes the strategic role of ML as a tool for achieving competitive advantages and suggests directions for further research in adapting these technologies to various industries.

This article proposes an information system specialized in the automatic detection of skin diseases, particularly melanoma, based on dermoscopic images. The system architecture is built on the integration of Laravel and Django frameworks through a RESTful API and is designed with a modular and scalable structure. The paper analyzes the technological advantages, functional capabilities, and practical applicability of the system in medical diagnostics.

The article describes the state of development of small business and private entrepreneurship and the factors affecting it, the socio-economic aspects of the development of the sector and the evaluation of structural changes.

One of the most important tasks is to constantly monitor changes in the greenhouse. If the greenhouse is small, we can manage it with one worker. But if the greenhouse is large, then its monitoring and management require a lot of time and human resources. Working in a greenhouse involves not only managing it, but also performing certain operations, such as: ventilation, water distribution, harvesting ripe crops, spraying chemicals against pests, etc. To automate and intelligently analyze these tasks, this paper considers a model of an agricultural robotic manipulator for a greenhouse.

The article discusses key aspects of the implementation of artificial intelligence in the educational process. Using the example of developing an online course on databases, the practical application of artificial intelligence is shown: material generation, automatic checking of assignments, chatbot, etc. Particular attention is paid to the role of artificial intelligence as a support tool for teaching.

This article examines the implementation of the k-means clustering algorithm for the detection of dynamic objects. Since k-means is one of the unsupervised learning methods, it is widely used in tasks that involve the real-time detection, tracking, and classification of moving objects. The essence of the method, its implementation, and its disadvantages indicate the need for approaches related to deep learning techniques.

Accurate assessment of athletes’ physical condition, including fatigue level, is essential for optimal training planning, achieving high performance, and reducing the risk of injury. Muscle biosignals, in particular electromyography (EMG), provide valuable information about muscle activity and fatigue. In recent years, artificial intelligence (Al) methods have become a powerful tool for analyzing these biosignals and automatically assessing fatigue. This article aims to analyze the effectiveness of various Al algorithms in assessing athlete fatigue based on EMG signals.

In today’s digital era, developing a user-friendly and efficient mobile application for local grocery markets is essential. OVVO is a mobile application designed for local grocery stores that integrates various features to enhance the shopping experience. This article highlights the design principles, functional components, and technologies implemented in the OVVO app, focusing on the minimalist interface, intuitive navigation, and seamless product browsing. The app includes sections like product categories, discounts, top-selling items, and a shopping cart with customizable collection options. It allows users to manage their purchases, track their order history, and engage with customer support through a chat feature.

This research work partially describes the elements of the knowledge base, which are widely used in decision-making processes in intelligent systems, the stages of their formation, and at the same time the sequences of enriching logical rules with predicates. In addition, the research includes the general architecture of intellectual systems based on the knowledge base and theoretical information about the types and properties of rules. At the same time, the article also includes an analysis of the main literature on the construction and enrichment of rules using the concepts and principles of first-order logic.

This study presents a state-of-the-art approach to optimize fuzzy inference systems (FIS) using genetic algorithms (GA), a powerful evolutionary method inspired by natural selection. Traditional FIS development relies on heuristic tuning of the rule base and relevance functions, which can be inefficient. This study systematically optimizes the FIS rule base, which improves the accuracy, flexibility, and robustness of decision systems. Experimental results show that the complexity of the rule base is significantly reduced while maintaining the system performance. The study also highlights the importance of GA operators such as selection, crossover, and mutation to achieve global optimality. Such integration helps develop intelligent systems that can adapt to real-world situations, yielding promising results for expert systems, automation, and control applications.

This paper focuses on the training data preparation stage of the CRISP-DM methodology in data mining. Because this stage takes up to 80% of the model development time, the steps of the training data preparation stage are explained with illustrations, approaches to training data in the model are presented, and considerations for machine learning engineers and data analysts are mentioned.

The paper presents a method for real-time control of hydraulic structures in open channels using a Multi-Layer Perceptron (MLP) and Artificial Neural Networks (ANN). The proposed ANN model, which is more efficient than traditional hydraulic models, is designed to predict gate status based on water level, flow rate, and demand.

This article analyzes the challenges encountered in the digital processing of images of human internal organs obtained through video endoscopy, as well as methods for addressing them. Although video endoscopic images are widely used in medicine for diagnostics and surgical planning, their quality can be degraded by factors such as insufficient lighting, noise, geometric distortions, and variations in color balance. Moreover, the biological variability of the human body and pathological differences in disease manifestation adversely affect the accuracy of artificial intelligence models. The article substantiates the relevance of applying modem algorithmic approaches, including deep learning technologies, to improve image quality and enhance diagnostic efficiency.