Vol. 26 No. 6 (2025)

Предтекстовый этап в обучении русскому языку как иностранному играет ключевую роль в формировании языковой компетенции учащихся. Он направлен на подготовку к восприятию и пониманию основного текста, активизацию фоновых знаний и развитие необходимых навыков. В статье рассматривается система упражнений, используемых на данном этапе, их классификация и методические принципы. Особое внимание уделяется лексико-грамматической подготовке, развитию прогнозирования и контекстного анализа. Приводятся примеры упражнений, а также анализируется их эффективность в учебном процессе.

Предтекстовый этап в обучении русскому языку как иностранному играет ключевую роль в формировании языковой компетенции учащихся. Он направлен на подготовку к восприятию и пониманию основного текста, активизацию фоновых знаний и развитие необходимых навыков. В статье рассматривается система упражнений, используемых на данном этапе, их классификация и методические принципы. Особое внимание уделяется лексико-грамматической подготовке, развитию прогнозирования и контекстного анализа. Приводятся примеры упражнений, а также анализируется их эффективность в учебном процессе.

This article analyzes the main models of knowledge presentation and their application. In connection with the development of educational methods and technologies, the importance of various models for the effective presentation of knowledge in the educational process is increasing. The article considers such models as traditional education, distance learning, blended learning (hybrid learning), experiential learning, constructivism, goal-oriented learning, project-based learning, and gamification. The article provides a comparative analysis of new approaches and methods in education, which are important in creating opportunities for students to acquire modern knowledge.

The article examines how artificial intelligence technologies can be used in the study of English Romanticism. English Romanticism is an important period of literature of the 18th and 19th centuries, which presents ideas such as nature, the human psyche, fantasy, and freedom. Artificial intelligence, in particular, through the use of natural language processing, data analysis, and generative models, helps to automate the analysis of romantic works, create new literary works, and gain a deeper understanding of the historical context. The article highlights the possibilities of using AI for methodological and semantic analysis of texts, creating advanced search systems in literary studies, and identifying literary motifs of the Romantic period.

The early detection of eye diseases plays a crucial role in preventing vision loss and improving treatment outcomes. With advancements in artificial intelligence (AI), particularly in machine learning and deep learning, it has become feasible to develop algorithms capable of identifying early signs of various eye conditions. This study presents an AI-based algorithm for detecting common eye diseases, such as diabetic retinopathy, glaucoma, and age-related macular degeneration (AMD). The proposed algorithm leverages convolutional neural networks (CNNs) to analyze medical imaging data, such as fundus photographs, optical coherence tomography (OCT), and visual field tests.

This article analyzes the benefits of knowledge bases and their management methods. The article examines the main benefits of knowledge bases, including the ability to systematically store knowledge, support innovation, make effective decisions, and develop skills. The article emphasizes the important role of knowledge management in increasing the competitiveness of organizations and improving their operational efficiency.

The article reviews algorithms for extracting informatics features from data using artificial intelligence methods. Extracting informatics features is the process of identifying important and useful information from a data set. This process is carried out, in particular, using natural language processing (NLP), machine learning (ML), and deep learning (DL) technologies. The article covers in detail the stages of data collection, preprocessing, feature extraction, and selection, as well as algorithms for extracting informatics features using machine learning and deep learning methods (e.g., SVM, KNN, CNN, RNN).

This article examines the role and importance of agent environments in society. Agent-based systems, with their autonomous and interactive features, are widely used in various areas of society. The article describes in detail how agents are used in modeling social systems, analyzing economic processes, predicting epidemics in healthcare, urban planning, and many other areas, and how they affect society.

The article presents the possibilities of intelligent data analysis, automatic data analysis, and extraction of useful knowledge from data, due to the fact that the amount of data generated around the world is very large and frequently updated, and the need to use advanced technologies such as artificial intelligence and machine learning in data collection and analysis.

The article states that intelligent agents, which are used in many fields, including robotics, medicine, finance, transportation, and e-commerce, are usually capable of self-learning and assimilating new knowledge, which increases their efficiency and adaptability. The article discusses the main types, technological foundations, applications, and future of intelligent agents.

В статье рассматривается актуальность использования технологий «Интернет вещей» (IoT) в системе электронного правительства (e-Government). Анализируются основные направления внедрения IoT, его влияние на цифровизацию государственного управления, повышение эффективности оказания государственных услуг и обеспечение безопасности данных.

The article discusses the basics and practical applications of disease detection based on neural networks. Neural networks, one of the most advanced branches of artificial intelligence, provide great opportunities for early detection of diseases in the medical field and effective organization of diagnostic processes. The article provides detailed information about the main types of neural networks, in particular, feedforward networks, convolutional networks (CNN), recurrent networks (RNN) and deep neural networks (DNN).

В данной статье проанализировано современное состояние продвижения продукции узбекских предприятий и показаны эффективные пути совершенствования. Также представлены практические примеры продвижения продукции, на основании которых даются рекомендации по развитию данной сферы в дальнейшем.

The rapid development of artificial intelligence (AI) has transformed various sectors, especially computer technologies, creating profound impacts on software, hardware, and computational systems. AI applications, such as machine learning, natural language processing, computer vision, and robotics, have revolutionized the way computers are used and have driven innovation in areas like data analysis, automation, and personalized experiences. This article explores the role of AI in modern computer technologies, highlights the key areas where it has made significant advancements, and discusses future prospects and challenges. The intersection of AI and computing holds the promise to continue shaping the technological landscape, offering new solutions to existing problems while presenting ethical and operational considerations.

The article analyzes the role of machine learning technology in society and its impact on various sectors. Machine learning technology helps create innovations in society, increase efficiency, reduce errors, and improve decision-making. The article also highlights the positive impact of machine learning on the development of society and its future potential.

The article presents how artificial intelligence technologies can be integrated into the educational process in technical schools and its role in improving the quality of education. The article also shows the importance of automatic assessment based on SI, the ability of teachers to effectively manage time and resources, and analytical approaches in analyzing the quality of education. The article concludes with the role of artificial intelligence in further improving the education system in technical schools in the future.

The article analyzes the importance and role of collaborative learning in society. It also highlights the role of collaborative learning in creating innovations and economic growth among specialists and groups from different strata of society. The article emphasizes the positive impact of collaborative learning in the development of society and its relevance.

The rapid advancement of 3D technologies has significantly transformed the multimedia industry, offering immersive experiences in entertainment, education, healthcare, and other sectors. This paper explores the role of 3D technologies in multimedia, highlighting key innovations, applications, and challenges. The study also examines how emerging trends in 3D graphics, virtual reality (VR), and augmented reality (AR) are shaping the future of digital content.

This article presents an analysis of the role of experimental learning in society, the importance of experiments in scientific, technological, social and medical fields. The widespread use of experiments in society and their importance in various fields are discussed, and experiments are used in scientific research to discover new knowledge and test existing theories.

Artificial intelligence (AI) has emerged as a transformative force in modern military operations, enhancing decision-making processes, operational efficiency, and the effectiveness of defense strategies. The application of AI in the military encompasses a wide range of areas, including autonomous weapons systems, cyber defense, intelligence gathering, logistics optimization, and battlefield management. This paper explores the various ways AI is integrated into military operations, focusing on the strategic advantages, challenges, and ethical considerations associated with its use. AI technologies, such as machine learning, computer vision, and natural language processing, are revolutionizing how military forces analyze data, conduct surveillance, and engage in combat. However, the integration of AI into military systems raises significant concerns related to security, accountability, and the potential for escalation of conflicts. This paper examines these issues and proposes recommendations for the responsible and ethical application of AI in the military, ensuring that it enhances national security while mitigating risks.

This article aims to analyze fuzzy knowledge models and their applications, new approaches to the process of learning, understanding, and using knowledge and information. These knowledge models are widely used in various fields of society, especially in education, scientific research, artificial intelligence, technology, and social systems.

Artificial Intelligence (AI) has made significant strides in various fields, one of the most promising applications being the creation and management of knowledge bases. Knowledge bases are crucial for managing large amounts of data, facilitating quick access to relevant information, and supporting decision-making processes across various domains. This article explores the methods for building and enhancing knowledge bases using AI, focusing on techniques such as machine learning, natural language processing (NLP), and semantic web technologies. By examining AI’s role in automating data extraction, knowledge representation, and reasoning processes, we highlight how AI can make knowledge bases more efficient, accurate, and adaptable. Additionally, the article discusses challenges in AI-driven knowledge base development and the future prospects of intelligent knowledge management systems.

The article explains in detail the importance of recurrent neural networks in various areas of society, their principles and types, how they are used in natural language processing, speech recognition, financial forecasting, the automotive industry, healthcare, video analysis, and many other areas. The prospects for improving existing technologies and creating new opportunities using RNNs are considered.

Convolutional neural networks are widely used in artificial intelligence and machine learning in image analysis, natural language processing, and other complex data processing. The main characteristics of CNNs are automatic feature learning, extraction of important elements in images and data, invariance, hierarchical feature detection, and efficient parameter sharing. This article provides detailed information on the working principle of convolutional neural networks, their layers (convolution, pooling, fully connected), as well as how they are used in real-world problems.

This article analyzes the working principle of neural networks and their role in society. Neural networks, as a key component of artificial intelligence and machine learning technologies, are revolutionizing many fields. The working principle of the network is based on the human brain, capable of learning, classifying, and making decisions based on data. It is effectively used in production optimization, medical diagnostics, creating personal assistants, and automation systems. The article also discusses the economic and social impact of neural networks on society, ethical issues, and future development prospects.

The article discusses the technologies that model the human brain, which are widely used in data analysis, data mining, and decision-making. In society, artificial neural networks are bringing revolutionary changes in the economy, healthcare, education, transportation, everyday life, and other areas. With the help of these technologies, production efficiency increases, medical diagnostics becomes more accurate, education is individualized, and automated transportation systems work efficiently. However, they also raise ethical, social, and economic issues. The article examines the positive and negative impacts of artificial neural networks on society and discusses the necessary measures for their future development..

The article analyzes the advantages of supervised learning algorithms. The article highlights the advantages of supervised learning algorithms in providing accurate and reliable results, assisting in data-based decision-making, reducing errors, and wide application areas.

This article analyzes the main types of machine learning and their importance in society. Machine learning technology, as an important part of artificial intelligence, is being effectively used in various fields. Types of machine learning, such as supervised learning, unsupervised learning, iterative learning, and reinforcement learning, play an important role in creating innovations in self-driving systems, healthcare, finance, education, and other areas.

The rapid growth of digital data necessitates efficient methods for processing large volumes of information. Machine knowledge, an advanced approach that integrates artificial intelligence (AI), machine learning (ML), and knowledge representation techniques, plays a crucial role in this process. This paper explores various methodologies for handling vast amounts of information, highlighting their effectiveness, advantages, and limitations.

The rapid expansion of big data necessitates advanced analytical approaches to extract meaningful insights. Data mindsighting, a novel concept integrating cognitive analytics, artificial intelligence (AI), and predictive modeling, plays a critical role in understanding and interpreting massive datasets. This paper explores the role and importance of data mindsighting in big data theory, its methodologies, applications, and future prospects.

В статье анализируется практическое применение технологии машинного обучения. В нем показано применение машинного обучения в таких областях, как здравоохранение, финансы, транспорт, образование, социальные сети и СМИ. В статье также подчеркивается роль машинного обучения в создании инноваций и повышении эффективности общества. Подчеркивается, что практическое применение этой технологии важно для развития общества и создания новых возможностей. Машины эффективно диагностируют заболевания, предотвращают мошенничество, создают автоматизированные системы и разрабатывают персонализированные системы обучения.

This article analyzes the types of economic agents and their applications in economic processes. Economic agents are consumers, producers, financial institutions, the state and other economic entities, each of which plays an important role in the economic system. Consumers form demand, producers form supply, and financial institutions play an important role in the allocation of resources. The state regulates the market through economic policy and ensures social stability.

The article presents the algorithm of operation of the perceptron, the necessary conditions and technical aspects for its correct operation. It also considers its application in various fields such as machine learning, classification, face recognition, and handwritten digit recognition. The perceptron is the basis for the development of modern artificial intelligence systems and is important as one of the main elements of deep learning.

With the increasing reliance on computer networks for data storage, transmission, and processing, ensuring data integrity and information security has become a critical concern. This paper explores fundamental concepts, key challenges, and advanced techniques used to maintain data integrity and protect information from cyber threats. We discuss encryption methods, access control mechanisms, intrusion detection systems, and emerging technologies such as blockchain and artificial intelligence (AI) in securing digital environments.

The rapid expansion of global communication networks has led to the proliferation of information objects, which play a crucial role in data exchange, knowledge dissemination, and digital interactions. This paper examines the nature, classification, and significance of information objects within the global communication infrastructure. It also explores the challenges associated with data security, integrity, and accessibility, as well as emerging trends in artificial intelligence and blockchain technologies for optimizing information management.

This article analyzes modern innovations such as the creation of electronic libraries, the process of digitization, the use of multimedia technologies, improving library services through mobile applications and interactive services. It also examines the role of social networks and online marketing in attracting users to libraries, the impact of technology on attracting young people to libraries, and the importance of integration with global information systems. The article presents important steps and approaches for libraries to attract readers through the use of modern technologies.

The processing of visual information plays a crucial role in various domains, including artificial intelligence, medical imaging, and computer vision. Despite significant advancements in computational power and algorithms, challenges persist in optimizing the accuracy, speed, and efficiency of visual data processing. This paper explores key issues related to optimal processing of visual information, including computational complexity, real-time performance, noise reduction, and data compression. It also discusses potential solutions and future research directions to enhance visual data analysis and interpretation.

This article presents an algorithm designed for extracting logical symbols from data using artificial intelligence methods. The approach leverages advanced techniques in machine learning, data processing, and pattern recognition to identify and classify logical symbols from complex datasets. The article also explores the potential applications of this algorithm in fields such as natural language processing, image recognition, and knowledge representation, providing insights into how artificial intelligence can transform the handling of logical data elements.

This article analyzes common cardiovascular diseases, their causes, prevention and treatment, preventive measures, and the organs in which the disease occurs, their structure and function. The article also examines methods for identifying and diagnosing circulatory system diseases based on international experience. The article discusses the function, importance, and mechanism of the cardiovascular system in the human body.

This article analyzes common cardiovascular diseases, their causes, prevention and treatment, preventive measures, and the organs in which the disease occurs, their structure and function. The article also examines methods for identifying and diagnosing circulatory system diseases based on international experience. The article discusses the function, importance, and mechanism of the cardiovascular system in the human body.

This article analyzes the importance of Deep Learning technologies in education today. Deep learning technologies are an advanced form of artificial intelligence that can work with large amounts of data. This technology is widely used to personalize the educational process, provide learning materials tailored to the needs of students, and develop interactive assistants. Deep learning methods also help teachers identify student achievement and analyze their learning activities. However, there are also problems in implementing these technologies, such as technical shortcomings, data security, and training teachers to work with technology. The article examines the conditions and opportunities necessary for the effective use of deep learning technologies in education.

Artificial intelligence is revolutionizing the ekonomy industry by enhancing content creation, distribution, and consumption processes. AI technologies, including machine learning, natural language processing, and computer vision, have made significant strides in improving automation, personalizing user experiences, and optimizing operations. This paper explores the transformative role of AI in ekonomy, focusing on its applications in content recommendation, live ekonomy, news generation, and audience analysis. We examine the impact of AI on production workflows, its potential for creating more engaging content, and its ability to improve decision-making for broadcasters and advertisers.

The article analyzes the application of artificial neural networks in society and its impact in various fields. Artificial neural networks are a technology based on modeling the activity of the human brain and are widely used in analyzing complex data, making decisions, and forecasting. In society, this technology is leading to revolutionary changes in the economy, healthcare, education, transport, everyday life, and other areas. With the help of artificial neural networks, production efficiency increases, medical diagnostics becomes more accurate, education is individualized, and transportation systems operate more efficiently. The article discusses the positive impact of artificial neural networks on society and the ethical and social problems of its development.

The article analyzes the principle of operation of artificial neural networks and their role in society. Artificial neural networks are technologies that model the activity of the human brain and are widely used in complex data processing, decision-making and forecasting. The article explains the basic principle of operation of artificial neural networks, namely the process of processing and learning incoming data through neurons. It discusses how artificial neural networks are used in various areas of society - economics, healthcare, education, transport and everyday life - and their social impact.

Structured search plays a vital role in modern information retrieval systems, enabling efficient and precise access to relevant data. Unlike unstructured search, structured search utilizes predefined data models, indexing techniques, and query languages to optimize search performance. This paper explores the core principles of structured search, including metadata usage, database indexing, query optimization, and machine learning integration. It also discusses challenges such as scalability, relevance ranking, and multi-source data aggregation in search systems

Artificial intelligence has become a pivotal force in revolutionizing various sectors, with television broadcasting being no exception. The integration of AI in television broadcasting systems has introduced significant advancements in content creation, distribution, viewer engagement, and overall production efficiency. This article explores the importance of AI in broadcasting, focusing on how it enhances the quality of content, personalizes viewer experiences, optimizes operational workflows, and aids in decision-making processes. By examining AI's role in automating tasks such as video editing, recommendation systems, and live broadcasting, we highlight its transformative effects on the industry. Furthermore, the article discusses the challenges and ethical considerations surrounding AI use in television, emphasizing the need for responsible implementation to ensure both innovation and fairness.

The article analyzes the principles of operation of Generative Adversarial Networks technology and its role in society. GANs are an artificial intelligence model based on the competition between generator and discriminator neural networks. This technology allows you to create new, realistic data, such as images, videos, music and other creative content. GANs technology also raises ethical and social issues, such as the harmful effects of deepfake technology. The article examines the positive and negative effects of GANs in various fields, their impact on society and future development prospects.

The article shows that solving mathematical problems can be more effectively implemented using artificial intelligence (AI) than traditional methods. Artificial intelligence, in particular neural networks and deep learning (Deep Learning) methods, significantly simplify and accelerate the process of solving mathematical and statistical problems. This work considers the application, capabilities and practical approaches of artificial intelligence methods in solving mathematical problems.

The article states that Artificial Intelligence technologies are currently bringing positive changes to various aspects of society, including production, education, healthcare, finance and public safety, and that economically, artificial intelligence is creating opportunities for automating production, creating innovative products and creating new jobs. The impact of artificial intelligence on the economic and social system, its advantages and problems are considered.

В условиях цифровой трансформации образования особую актуальность приобретает интеграция информационно-коммуникационных технологий (ИКТ) в преподавание школьных и вузовских дисциплин. Математика, как одна из важнейших фундаментальных наук, требует не только абстрактного мышления, но и практико-ориентированного подхода в обучении. В данной статье рассматривается значение ИКТ в обучении математике, их функции, конкретные инструменты и технологии, а также потенциальные трудности и пути их преодоления. Особое внимание уделено роли ИКТ в формировании ключевых компетенций учащихся, таких как аналитическое мышление, цифровая грамотность и способность к самообучению.

The integration of artificial intelligence (AI) into database management and design has significantly enhanced the efficiency and accuracy of data organization, analysis, and storage. This article presents an algorithm for forming databases using AI techniques, focusing on machine learning, clustering, and data mining methods. The proposed algorithm automates the process of structuring and managing large datasets, improving the decision-making capabilities of database systems. By employing AI models, such as neural networks and support vector machines, the algorithm adapts to evolving data patterns and ensures optimal organization of information. This work explores the underlying AI principles used in database formation, highlights the key benefits, and outlines challenges in applying these technologies to real-world database systems.

Scientific calculations play a crucial role in various fields, including physics, engineering, and data analysis. The use of software tools significantly enhances the accuracy, efficiency, and reproducibility of these calculations. This paper examines the role of software tools in scientific computations, discusses their advantages, and explores key applications in different domains. Furthermore, it reviews emerging trends in computational science, including artificial intelligence and cloud computing for large-scale calculations.

This article analyzes the importance of Deep Learning technologies in education today. Deep learning technologies are an advanced form of artificial intelligence that can work with large amounts of data. This technology is widely used to personalize the educational process, provide learning materials tailored to the needs of students, and develop interactive assistants. Deep learning methods also help teachers identify student achievement and analyze their learning activities. However, there are also problems in implementing these technologies, such as technical shortcomings, data security, and training teachers to work with technology. The article examines the conditions and opportunities necessary for the effective use of deep learning technologies in education.

Software requirements serve as the foundation for successful software development, ensuring alignment between stakeholders' needs and system functionality. This paper explores the different levels of software requirements, including business, user, and system requirements, as well as their hierarchical structure. It also discusses best practices for requirement elicitation, specification, and validation to enhance software quality and project success.

Tafakkur — bu aqliy faoliyatning asosiy shakli bo‘lib, insonlarning hayotdagi qarorlar qabul qilish, muammolarni hal qilish va o‘zgarishlarga moslashish qobiliyatlarini shakllantiradi. Ijodiy, tanqidiy va reflektiv tafakkur ko‘nikmalarini rivojlantirish insonning aqliy salohiyatini oshiradi va kundalik hayotda muvaffaqiyatga erishishga yordam beradi.

Ushbu maqola bolalarda sezgi va idrok kabi psixik jarayonlarning rivojlanish xususiyatlarini psixodiagnostika qilishga bagʻishlangan. Unda sezgi va idrok tushunchalari, ularning bolaning aqliy, nutqiy va ijtimoiy-emotsional rivojlanishidagi fundamental ahamiyati koʻrib chiqiladi. Shuningdek, ushbu bilish jarayonlarining yosh davrlariga mos ravishda kechishi, diagnostika qilishning asosiy metodlari (kuzatish, eksperimental-oʻyin metodikalari, standartlashtirilgan testlar) atroflicha yoritilgan. Maqolada diagnostika natijalarini sifatli va miqdoriy tahlil qilish, aniqlangan kamchiliklarni bartaraf etishga qaratilgan korreksion-rivojlantiruvchi ishlar tizimi (sensor oʻyinlar, didaktik materiallar, ota-onalar va mutaxassislar bilan hamkorlik) batafsil bayon etilgan. Maqola psixologlar, pedagoglar, defektologlar hamda bolalarning rivojlanishiga qiziqadigan ota-onalar uchun foydali boʻlishi mumkin.

Ushbu maqolada maktabgacha yoshdagi bolalarda boshlang‘ich matematik tasavvurlarni shakllantirish jarayonida maktabgacha ta’lim tashkiloti va oila o‘rtasidagi o‘zaro hamkorlikning roli va ahamiyati yoritilgan. Maqolada bolalarning yosh xususiyatlari, kognitiv rivojlanish bosqichlari, matematik tafakkurning shakllanishi, ta’lim muassasasining metodik yondashuvlari hamda oilaning amaliy ishtiroki chuqur tahlil qilinadi. Shuningdek, pedagoglar va ota-onalar o‘rtasidagi integratsiyalashgan hamkorlikning samarali shakllari, raqamli vositalar yordamida tashkil etilayotgan kommunikatsiya usullari ko‘rib chiqiladi. Maqola zamonaviy pedagogik yondashuvlarga asoslangan bo‘lib, ta’lim sifati va bola shaxsining kompleks rivojlanishini ta’minlashda uzviy hamkorlikning zarurligini asoslaydi.

The integration of traditional medicine into nursing education is essential for providing holistic care that respects cultural diversity and enhances patient outcomes. This paper explores various pedagogical approaches and methods for teaching traditional medicine within nursing curricula, emphasizing experiential learning, interprofessional education, and the incorporation of complementary therapies.

Ushbu maqolada XVI–XVIII asrlarda Buxoro xonligi va Hindiston o‘rtasidagi diplomatik munosabatlarning shakllanishi, rivojlanish bosqichlari, elchilik missiyalari va savdo-iqtisodiy hamkorlikning asosiy jihatlari ilmiy asosda tahlil qilinadi.

Ushbu ishda menejer shaxsining ijtimoiy-psixologik xususiyatlari yoritilgan. Boshqaruv jarayonida menejerning liderlik salohiyati, muloqot madaniyati, hissiy intellekti, tashkiliy va tashabbuskorlik qobiliyatlari asosiy omillar sifatida ko‘rib chiqilgan.  Menejerlik faoliyatini qo’llash bo’yicha ko’nikmalar berilgan. Menejerni psixologik sifatlariga to’xtalib o’tilgan.

Maqolada bitiruvchilar va ish beruvchilar o‘rtasidagi o‘zaro axborot almashinuvi asosida samarali va avtomatlashtirilgan muvofiqlashtirish algoritmlarini ishlab chiqish konsepsiyasi bayon etiladi. Har ikki tomonning ehtiyoj va imkoniyatlarini aniqlovchi, baholovchi va muvofiqlashtiruvchi algoritmik yondashuvlar tahlil qilinadi. Shuningdek, ushbu tizim orqali oliy ta’lim tizimi va mehnat bozorining o‘zaro integratsiyasini ta’minlash mexanizmlari yoritiladi.

Artificial intelligence is revolutionizing the ekonomy industry by enhancing content creation, distribution, and consumption processes. AI technologies, including machine learning, natural language processing, and computer vision, have made significant strides in improving automation, personalizing user experiences, and optimizing operations. This paper explores the transformative role of AI in ekonomy, focusing on its applications in content recommendation, live ekonomy, news generation, and audience analysis. We examine the impact of AI on production workflows, its potential for creating more engaging content, and its ability to improve decision-making for broadcasters and advertisers.

The article analyzes the application of artificial neural networks in society and its impact in various fields. Artificial neural networks are a technology based on modeling the activity of the human brain and are widely used in analyzing complex data, making decisions, and forecasting. In society, this technology is leading to revolutionary changes in the economy, healthcare, education, transport, everyday life, and other areas. With the help of artificial neural networks, production efficiency increases, medical diagnostics becomes more accurate, education is individualized, and transportation systems operate more efficiently. The article discusses the positive impact of artificial neural networks on society and the ethical and social problems of its development.

The article analyzes the principle of operation of artificial neural networks and their role in society. Artificial neural networks are technologies that model the activity of the human brain and are widely used in complex data processing, decision-making and forecasting. The article explains the basic principle of operation of artificial neural networks, namely the process of processing and learning incoming data through neurons. It discusses how artificial neural networks are used in various areas of society - economics, healthcare, education, transport and everyday life - and their social impact.

Structured search plays a vital role in modern information retrieval systems, enabling efficient and precise access to relevant data. Unlike unstructured search, structured search utilizes predefined data models, indexing techniques, and query languages to optimize search performance. This paper explores the core principles of structured search, including metadata usage, database indexing, query optimization, and machine learning integration. It also discusses challenges such as scalability, relevance ranking, and multi-source data aggregation in search systems

Artificial intelligence has become a pivotal force in revolutionizing various sectors, with television broadcasting being no exception. The integration of AI in television broadcasting systems has introduced significant advancements in content creation, distribution, viewer engagement, and overall production efficiency. This article explores the importance of AI in broadcasting, focusing on how it enhances the quality of content, personalizes viewer experiences, optimizes operational workflows, and aids in decision-making processes. By examining AI's role in automating tasks such as video editing, recommendation systems, and live broadcasting, we highlight its transformative effects on the industry. Furthermore, the article discusses the challenges and ethical considerations surrounding AI use in television, emphasizing the need for responsible implementation to ensure both innovation and fairness.

The article analyzes the principles of operation of Generative Adversarial Networks technology and its role in society. GANs are an artificial intelligence model based on the competition between generator and discriminator neural networks. This technology allows you to create new, realistic data, such as images, videos, music and other creative content. GANs technology also raises ethical and social issues, such as the harmful effects of deepfake technology. The article examines the positive and negative effects of GANs in various fields, their impact on society and future development prospects.

The article shows that solving mathematical problems can be more effectively implemented using artificial intelligence (AI) than traditional methods. Artificial intelligence, in particular neural networks and deep learning (Deep Learning) methods, significantly simplify and accelerate the process of solving mathematical and statistical problems. This work considers the application, capabilities and practical approaches of artificial intelligence methods in solving mathematical problems.

The article states that Artificial Intelligence technologies are currently bringing positive changes to various aspects of society, including production, education, healthcare, finance and public safety, and that economically, artificial intelligence is creating opportunities for automating production, creating innovative products and creating new jobs. The impact of artificial intelligence on the economic and social system, its advantages and problems are considered.

В условиях цифровой трансформации образования особую актуальность приобретает интеграция информационно-коммуникационных технологий (ИКТ) в преподавание школьных и вузовских дисциплин. Математика, как одна из важнейших фундаментальных наук, требует не только абстрактного мышления, но и практико-ориентированного подхода в обучении. В данной статье рассматривается значение ИКТ в обучении математике, их функции, конкретные инструменты и технологии, а также потенциальные трудности и пути их преодоления. Особое внимание уделено роли ИКТ в формировании ключевых компетенций учащихся, таких как аналитическое мышление, цифровая грамотность и способность к самообучению.

The integration of artificial intelligence (AI) into database management and design has significantly enhanced the efficiency and accuracy of data organization, analysis, and storage. This article presents an algorithm for forming databases using AI techniques, focusing on machine learning, clustering, and data mining methods. The proposed algorithm automates the process of structuring and managing large datasets, improving the decision-making capabilities of database systems. By employing AI models, such as neural networks and support vector machines, the algorithm adapts to evolving data patterns and ensures optimal organization of information. This work explores the underlying AI principles used in database formation, highlights the key benefits, and outlines challenges in applying these technologies to real-world database systems.

Scientific calculations play a crucial role in various fields, including physics, engineering, and data analysis. The use of software tools significantly enhances the accuracy, efficiency, and reproducibility of these calculations. This paper examines the role of software tools in scientific computations, discusses their advantages, and explores key applications in different domains. Furthermore, it reviews emerging trends in computational science, including artificial intelligence and cloud computing for large-scale calculations.

This article analyzes the importance of Deep Learning technologies in education today. Deep learning technologies are an advanced form of artificial intelligence that can work with large amounts of data. This technology is widely used to personalize the educational process, provide learning materials tailored to the needs of students, and develop interactive assistants. Deep learning methods also help teachers identify student achievement and analyze their learning activities. However, there are also problems in implementing these technologies, such as technical shortcomings, data security, and training teachers to work with technology. The article examines the conditions and opportunities necessary for the effective use of deep learning technologies in education.

Software requirements serve as the foundation for successful software development, ensuring alignment between stakeholders' needs and system functionality. This paper explores the different levels of software requirements, including business, user, and system requirements, as well as their hierarchical structure. It also discusses best practices for requirement elicitation, specification, and validation to enhance software quality and project success.

This article analyzes the types of economic agents and their applications in economic processes. Economic agents are consumers, producers, financial institutions, the state and other economic entities, each of which plays an important role in the economic system. Consumers form demand, producers form supply, and financial institutions play an important role in the allocation of resources. The state regulates the market through economic policy and ensures social stability.

The article presents the algorithm of operation of the perceptron, the necessary conditions and technical aspects for its correct operation. It also considers its application in various fields such as machine learning, classification, face recognition, and handwritten digit recognition. The perceptron is the basis for the development of modern artificial intelligence systems and is important as one of the main elements of deep learning.

With the increasing reliance on computer networks for data storage, transmission, and processing, ensuring data integrity and information security has become a critical concern. This paper explores fundamental concepts, key challenges, and advanced techniques used to maintain data integrity and protect information from cyber threats. We discuss encryption methods, access control mechanisms, intrusion detection systems, and emerging technologies such as blockchain and artificial intelligence (AI) in securing digital environments.

The rapid expansion of global communication networks has led to the proliferation of information objects, which play a crucial role in data exchange, knowledge dissemination, and digital interactions. This paper examines the nature, classification, and significance of information objects within the global communication infrastructure. It also explores the challenges associated with data security, integrity, and accessibility, as well as emerging trends in artificial intelligence and blockchain technologies for optimizing information management.

This article analyzes modern innovations such as the creation of electronic libraries, the process of digitization, the use of multimedia technologies, improving library services through mobile applications and interactive services. It also examines the role of social networks and online marketing in attracting users to libraries, the impact of technology on attracting young people to libraries, and the importance of integration with global information systems. The article presents important steps and approaches for libraries to attract readers through the use of modern technologies.

The processing of visual information plays a crucial role in various domains, including artificial intelligence, medical imaging, and computer vision. Despite significant advancements in computational power and algorithms, challenges persist in optimizing the accuracy, speed, and efficiency of visual data processing. This paper explores key issues related to optimal processing of visual information, including computational complexity, real-time performance, noise reduction, and data compression. It also discusses potential solutions and future research directions to enhance visual data analysis and interpretation.

This article presents an algorithm designed for extracting logical symbols from data using artificial intelligence methods. The approach leverages advanced techniques in machine learning, data processing, and pattern recognition to identify and classify logical symbols from complex datasets. The article also explores the potential applications of this algorithm in fields such as natural language processing, image recognition, and knowledge representation, providing insights into how artificial intelligence can transform the handling of logical data elements.

This article analyzes common cardiovascular diseases, their causes, prevention and treatment, preventive measures, and the organs in which the disease occurs, their structure and function. The article also examines methods for identifying and diagnosing circulatory system diseases based on international experience. The article discusses the function, importance, and mechanism of the cardiovascular system in the human body.

This article analyzes common cardiovascular diseases, their causes, prevention and treatment, preventive measures, and the organs in which the disease occurs, their structure and function. The article also examines methods for identifying and diagnosing circulatory system diseases based on international experience. The article discusses the function, importance, and mechanism of the cardiovascular system in the human body.

This article analyzes the importance of Deep Learning technologies in education today. Deep learning technologies are an advanced form of artificial intelligence that can work with large amounts of data. This technology is widely used to personalize the educational process, provide learning materials tailored to the needs of students, and develop interactive assistants. Deep learning methods also help teachers identify student achievement and analyze their learning activities. However, there are also problems in implementing these technologies, such as technical shortcomings, data security, and training teachers to work with technology. The article examines the conditions and opportunities necessary for the effective use of deep learning technologies in education.

Artificial Intelligence (AI) has made significant strides in various fields, one of the most promising applications being the creation and management of knowledge bases. Knowledge bases are crucial for managing large amounts of data, facilitating quick access to relevant information, and supporting decision-making processes across various domains. This article explores the methods for building and enhancing knowledge bases using AI, focusing on techniques such as machine learning, natural language processing (NLP), and semantic web technologies. By examining AI’s role in automating data extraction, knowledge representation, and reasoning processes, we highlight how AI can make knowledge bases more efficient, accurate, and adaptable. Additionally, the article discusses challenges in AI-driven knowledge base development and the future prospects of intelligent knowledge management systems.

The article explains in detail the importance of recurrent neural networks in various areas of society, their principles and types, how they are used in natural language processing, speech recognition, financial forecasting, the automotive industry, healthcare, video analysis, and many other areas. The prospects for improving existing technologies and creating new opportunities using RNNs are considered.

Convolutional neural networks are widely used in artificial intelligence and machine learning in image analysis, natural language processing, and other complex data processing. The main characteristics of CNNs are automatic feature learning, extraction of important elements in images and data, invariance, hierarchical feature detection, and efficient parameter sharing. This article provides detailed information on the working principle of convolutional neural networks, their layers (convolution, pooling, fully connected), as well as how they are used in real-world problems.

This article analyzes the working principle of neural networks and their role in society. Neural networks, as a key component of artificial intelligence and machine learning technologies, are revolutionizing many fields. The working principle of the network is based on the human brain, capable of learning, classifying, and making decisions based on data. It is effectively used in production optimization, medical diagnostics, creating personal assistants, and automation systems. The article also discusses the economic and social impact of neural networks on society, ethical issues, and future development prospects.

The article discusses the technologies that model the human brain, which are widely used in data analysis, data mining, and decision-making. In society, artificial neural networks are bringing revolutionary changes in the economy, healthcare, education, transportation, everyday life, and other areas. With the help of these technologies, production efficiency increases, medical diagnostics becomes more accurate, education is individualized, and automated transportation systems work efficiently. However, they also raise ethical, social, and economic issues. The article examines the positive and negative impacts of artificial neural networks on society and discusses the necessary measures for their future development..

The article analyzes the advantages of supervised learning algorithms. The article highlights the advantages of supervised learning algorithms in providing accurate and reliable results, assisting in data-based decision-making, reducing errors, and wide application areas.

This article analyzes the main types of machine learning and their importance in society. Machine learning technology, as an important part of artificial intelligence, is being effectively used in various fields. Types of machine learning, such as supervised learning, unsupervised learning, iterative learning, and reinforcement learning, play an important role in creating innovations in self-driving systems, healthcare, finance, education, and other areas.

The rapid growth of digital data necessitates efficient methods for processing large volumes of information. Machine knowledge, an advanced approach that integrates artificial intelligence (AI), machine learning (ML), and knowledge representation techniques, plays a crucial role in this process. This paper explores various methodologies for handling vast amounts of information, highlighting their effectiveness, advantages, and limitations.

The rapid expansion of big data necessitates advanced analytical approaches to extract meaningful insights. Data mindsighting, a novel concept integrating cognitive analytics, artificial intelligence (AI), and predictive modeling, plays a critical role in understanding and interpreting massive datasets. This paper explores the role and importance of data mindsighting in big data theory, its methodologies, applications, and future prospects.

В статье анализируется практическое применение технологии машинного обучения. В нем показано применение машинного обучения в таких областях, как здравоохранение, финансы, транспорт, образование, социальные сети и СМИ. В статье также подчеркивается роль машинного обучения в создании инноваций и повышении эффективности общества. Подчеркивается, что практическое применение этой технологии важно для развития общества и создания новых возможностей. Машины эффективно диагностируют заболевания, предотвращают мошенничество, создают автоматизированные системы и разрабатывают персонализированные системы обучения.

В данной статье проанализировано современное состояние продвижения продукции узбекских предприятий и показаны эффективные пути совершенствования. Также представлены практические примеры продвижения продукции, на основании которых даются рекомендации по развитию данной сферы в дальнейшем.

The rapid development of artificial intelligence (AI) has transformed various sectors, especially computer technologies, creating profound impacts on software, hardware, and computational systems. AI applications, such as machine learning, natural language processing, computer vision, and robotics, have revolutionized the way computers are used and have driven innovation in areas like data analysis, automation, and personalized experiences. This article explores the role of AI in modern computer technologies, highlights the key areas where it has made significant advancements, and discusses future prospects and challenges. The intersection of AI and computing holds the promise to continue shaping the technological landscape, offering new solutions to existing problems while presenting ethical and operational considerations.

The article analyzes the role of machine learning technology in society and its impact on various sectors. Machine learning technology helps create innovations in society, increase efficiency, reduce errors, and improve decision-making. The article also highlights the positive impact of machine learning on the development of society and its future potential.

The article presents how artificial intelligence technologies can be integrated into the educational process in technical schools and its role in improving the quality of education. The article also shows the importance of automatic assessment based on SI, the ability of teachers to effectively manage time and resources, and analytical approaches in analyzing the quality of education. The article concludes with the role of artificial intelligence in further improving the education system in technical schools in the future.

The article analyzes the importance and role of collaborative learning in society. It also highlights the role of collaborative learning in creating innovations and economic growth among specialists and groups from different strata of society. The article emphasizes the positive impact of collaborative learning in the development of society and its relevance.

The rapid advancement of 3D technologies has significantly transformed the multimedia industry, offering immersive experiences in entertainment, education, healthcare, and other sectors. This paper explores the role of 3D technologies in multimedia, highlighting key innovations, applications, and challenges. The study also examines how emerging trends in 3D graphics, virtual reality (VR), and augmented reality (AR) are shaping the future of digital content.

This article presents an analysis of the role of experimental learning in society, the importance of experiments in scientific, technological, social and medical fields. The widespread use of experiments in society and their importance in various fields are discussed, and experiments are used in scientific research to discover new knowledge and test existing theories.

Artificial intelligence (AI) has emerged as a transformative force in modern military operations, enhancing decision-making processes, operational efficiency, and the effectiveness of defense strategies. The application of AI in the military encompasses a wide range of areas, including autonomous weapons systems, cyber defense, intelligence gathering, logistics optimization, and battlefield management. This paper explores the various ways AI is integrated into military operations, focusing on the strategic advantages, challenges, and ethical considerations associated with its use. AI technologies, such as machine learning, computer vision, and natural language processing, are revolutionizing how military forces analyze data, conduct surveillance, and engage in combat. However, the integration of AI into military systems raises significant concerns related to security, accountability, and the potential for escalation of conflicts. This paper examines these issues and proposes recommendations for the responsible and ethical application of AI in the military, ensuring that it enhances national security while mitigating risks.

This article aims to analyze fuzzy knowledge models and their applications, new approaches to the process of learning, understanding, and using knowledge and information. These knowledge models are widely used in various fields of society, especially in education, scientific research, artificial intelligence, technology, and social systems.

This article analyzes the main models of knowledge presentation and their application. In connection with the development of educational methods and technologies, the importance of various models for the effective presentation of knowledge in the educational process is increasing. The article considers such models as traditional education, distance learning, blended learning (hybrid learning), experiential learning, constructivism, goal-oriented learning, project-based learning, and gamification. The article provides a comparative analysis of new approaches and methods in education, which are important in creating opportunities for students to acquire modern knowledge.

The article examines how artificial intelligence technologies can be used in the study of English Romanticism. English Romanticism is an important period of literature of the 18th and 19th centuries, which presents ideas such as nature, the human psyche, fantasy, and freedom. Artificial intelligence, in particular, through the use of natural language processing, data analysis, and generative models, helps to automate the analysis of romantic works, create new literary works, and gain a deeper understanding of the historical context. The article highlights the possibilities of using AI for methodological and semantic analysis of texts, creating advanced search systems in literary studies, and identifying literary motifs of the Romantic period.

This article analyzes the benefits of knowledge bases and their management methods. The article examines the main benefits of knowledge bases, including the ability to systematically store knowledge, support innovation, make effective decisions, and develop skills. The article emphasizes the important role of knowledge management in increasing the competitiveness of organizations and improving their operational efficiency.

The article reviews algorithms for extracting informatics features from data using artificial intelligence methods. Extracting informatics features is the process of identifying important and useful information from a data set. This process is carried out, in particular, using natural language processing (NLP), machine learning (ML), and deep learning (DL) technologies. The article covers in detail the stages of data collection, preprocessing, feature extraction, and selection, as well as algorithms for extracting informatics features using machine learning and deep learning methods (e.g., SVM, KNN, CNN, RNN).

This article examines the role and importance of agent environments in society. Agent-based systems, with their autonomous and interactive features, are widely used in various areas of society. The article describes in detail how agents are used in modeling social systems, analyzing economic processes, predicting epidemics in healthcare, urban planning, and many other areas, and how they affect society.

The article presents the possibilities of intelligent data analysis, automatic data analysis, and extraction of useful knowledge from data, due to the fact that the amount of data generated around the world is very large and frequently updated, and the need to use advanced technologies such as artificial intelligence and machine learning in data collection and analysis.

The article states that intelligent agents, which are used in many fields, including robotics, medicine, finance, transportation, and e-commerce, are usually capable of self-learning and assimilating new knowledge, which increases their efficiency and adaptability. The article discusses the main types, technological foundations, applications, and future of intelligent agents.

В статье рассматривается актуальность использования технологий «Интернет вещей» (IoT) в системе электронного правительства (e-Government). Анализируются основные направления внедрения IoT, его влияние на цифровизацию государственного управления, повышение эффективности оказания государственных услуг и обеспечение безопасности данных.

The article discusses the basics and practical applications of disease detection based on neural networks. Neural networks, one of the most advanced branches of artificial intelligence, provide great opportunities for early detection of diseases in the medical field and effective organization of diagnostic processes. The article provides detailed information about the main types of neural networks, in particular, feedforward networks, convolutional networks (CNN), recurrent networks (RNN) and deep neural networks (DNN).

The article discusses the basics and practical applications of disease detection based on neural networks. The article provides detailed information about the main types of neural networks, in particular, feedforward networks, convolutional networks (CNN), recurrent networks (RNN) and deep neural networks (DNN). It also analyzes the application of these networks in such fields as oncology, cardiology, neurology, endocrinology and infectious diseases, their effectiveness and advantages in disease detection. The article also reviews the widespread use of neural networks in medicine, along with limitations, data security and understandability issues.

The article presents information about the methods and stages of development of data intelligence analysis, which allows using modern technologies to effectively analyze data and extract useful knowledge from it, and how the updating of technologies and methods helps to make the analysis more accurate and effective. With new technologies and innovations, the application will be further expanded, and it will be possible to achieve effective results in various aspects of life around the world.

The article notes that today the Turing test has undergone several modifications and is used to evaluate many systems, including chatbots and virtual assistants. It is noted that the use of the Turing test in the development of artificial intelligence and its capabilities relative to humans is important not only in scientific research, but also in the field of information technology, in practical testing of artificial intelligence and the creation of real-life systems.

This article analyzes the development trends of artificial intelligence technologies. It discusses the development of artificial intelligence in learning and decision-making, natural language processing, automated systems and robotics, and the impact of high-level automation and the workforce. The article analyzes the current and future trends of artificial intelligence, its opportunities and risks, as well as its role in society.

This article discusses artificial intelligence (AI) as one of the central directions of technological development in recent years. The development of AI technologies is leading to profound changes in various areas of society. Its main goal is to simulate human mental activity, as well as to help solve complex problems. Understanding the role of AI systems in society, their tasks and prospects is important not only from a technological, but also from a social, economic and ethical perspective.

This article explores the widespread use of Artificial Intelligence  technologies and tools across various sectors. It provides an overview of key AI technologies such as Machine Learning, Deep Learning, Natural Language Processing, and Computer Vision, explaining their fundamental principles and applications. The article delves into how AI is transforming industries like healthcare, automotive, finance, education, and marketing, showcasing its potential to enhance efficiency, innovation, and decision-making processes. Additionally, the article addresses the challenges and ethical concerns related to AI, including data security, job displacement, and the potential for incorrect data analysis. Overall, the article emphasizes the significant role of AI in shaping future technological advancements and highlights the need for careful integration and regulation to ensure its positive impact on society.

In this article, we will cover the topic "Using C# Programming Languages ​​to Solve Problems with Remarkable Limits" and analyze the conveniences that the C# programming language provides in solving scientific calculations and limit problems.

В статье рассматриваются ключевые критерии отбора текста для учебного процесса при преподавании русского языка как иностранного (РКИ). Ведется анализ важнейших факторов, влияющих на выбор текстов для студентов, изучающих русский язык, таких как уровень языковой подготовки, культурные особенности, а также коммуникативная цель. Охарактеризованы различные виды текстов, которые могут быть использованы в зависимости от этапа обучения: от начального до продвинутого уровня. Также представлена роль текстов в формировании языковых навыков и их влиянии на развитие языковой компетенции обучающихся. Уделено внимание проблемам, связанным с актуальностью и доступностью текстов для изучающих русский язык в разных странах и культурных контекстах.

Заглавие текста играет важную роль в процессе обучения русскому языку как иностранному, оказывая влияние на формирование прогнозирующих навыков учащихся и их способность к смысловому восприятию текста. В данной статье рассматривается феномен заглавия как «нераскрытого содержания текста» и его роль в обучении иностранцев русскому языку. Анализируются методические подходы к использованию заголовков в предтекстовом этапе, их влияние на когнитивную активность учащихся и развитие критического мышления. Особое внимание уделяется практике работы с заголовками в коммуникативной методике преподавания РКИ.