American Journal of Technology and Applied Sciences
type: channel
description: American Journal of Technology and Applied Sciences is an peer reviewed international, open access journal. This journal publishes the articles in the field of Technology and Applied Sciences. Authors are requested to submit their original research for the double blind peer reviewed journal. ISSN (E): 2832-1766 JIF 2024: 9.115
publisher: American Journals Publishing
language: en
publication name: American Journal of Technology and Applied Sciences
issn: 2832-1766
items: DIGITAL TRANSFORMATION OF BUSINESS BASED ON INFORMATION TECHNOLOGY
items: GAMIFICATION IN DIGITAL MARKETING AS A TOOL FOR CONSUMER ENGAGEMENT
items: RAINY SEASON DISTRIBUTION OF HEAVY-METAL POLLUTION INDEX ALONG OKULU RIVERS IN ELEME LGA OF RIVERS STATE, NIGERIA
items: SPECTRAL PROPERTIES OF SELF-ADJOINT PARTIAL INTEGRAL OPERATORS WITH KERNELS BELONGING TO A SPECIFIC FUNCTION CLASS
items: ECONOMETRIC MODELING OF THE MAIN DETERMINANTS OF HOUSING PROVISION LEVEL
items: ADOPTION OF ARTIFICIAL INTELLIGENCE IN PREDICTIVE RISK ASSESSMENT IN SELECTED OIL AND GAS COMPANIES IN NIGERIA
items: MACHINE LEARNING-BASED DETECTION OF MALICIOUS WEB REQUESTS USING HTTP TRAFFIC FEATURES
items: EVALUATION OF THE EFFECTIVENESS OF STRENGTHENING BRICK MASONRY WITH GLASS-FIBER COMPOSITE REINFORCEMENT BASED ON EXPERIMENTAL TESTS
items: REGENERATION EFFICIENCY AND LONG-TERM STABILITY OF FE-MOFS FOR REPEATED NUTRIENT ADSORPTION CYCLES
items: INTELLIGENT ALGORITHMS FOR PERSONALIZED TRAVEL ROUTE PLANNING A GRAPH NEURAL NETWORK AND HYBRID MOVNS-A* APPROACH
items: FORMATION OF INFORMATION MODELING COMPETENCE IN THE PROCESS OF PHYSICS EDUCATION
items: THE ROLE OF ARTIFICIAL INTELLIGENCE IN IMPROVING CARDIOVASCULAR FUNCTION
items: INTEGRATION OF DISCIPLINES IN TEACHING CHEMICAL BONDING AND VALENCE IN ATOMIC PHYSICS
items: NEGATIVE AND POSITIVE EFFECTS OF USING AN ELECTRONIC DIGITAL SIGNATURE
items: USE OF ARTIFICIAL INTELLIGENCE IN THE DEVELOPMENT OF AUTOMATED INFORMATION SYSTEMS
items: DEVELOPING PRACTICAL COMPETENCE IN PHYSICS LABORATORY INSTRUCTION THROUGH MULTIFUNCTIONAL PROFESSIONALLY ORIENTED TASKS: A COMPETENCY-BASED DIDACTIC MODEL
items: THE ROLE OF TET2 MUTATIONS IN THE DEVELOPMENT OF CHIP-ASSOCIATED ATHEROSCLEROSIS
items: INFORMATION AND LEGAL RELATIONS OF THE E-STATE IN THE CONCEPT OF E-GOVERNMENT
items: SCHEMATIC ORGANIZATION OF THE SCIENTIFIC POTENTIAL OF PROFESSORS AND TEACHERS THROUGH TALENTED STUDENTS
items: DEVELOPING MECHANISMS FOR DEVELOPING THE TOURISM INDUSTRY BASED ON ARTIFICIAL INTELLIGENCE
items: METHODOLOGY FOR DEVELOPING PRACTICAL COMPETENCIES OF STUDENTS IN TEACHING THE DISCIPLINE "COMPUTER NETWORKS" BASED ON THE INTEGRATION OF GENERATIVE ARTIFICIAL INTELLIGENCE AND CISCO PACKET TRACER
items: PREPARATION OF MODERN PRESENTATIONS IN THE EDUCATIONAL PROCESS, OPPORTUNITIES AND PRACTICAL APPROACHES
items: MODERN TYPES OF DATABASE MANAGEMENT SYSTEMS AND THEIR CAPABILITIES
items: METHODS FOR SOLVING ECONOMIC PROBLEMS USING ARTIFICIAL INTELLIGENCE
items: DATABASE MODELS AND THE ENTITY-RELATIONSHIP MODEL
items: METHODS AND APPLICATIONS OF USING ARTIFICIAL INTELLIGENCE IN SOLVING PROBLEMS OF THE DIGITAL ECONOMY
items: INFORMATION SYSTEMS AND SOFTWARE IN DATABASE CREATION
items: DATABASE MANAGEMENT AND ANALYSIS WITH THE HELP OF ARTIFICIAL INTELLIGENCE

DIGITAL TRANSFORMATION OF BUSINESS BASED ON INFORMATION TECHNOLOGY
type: item
description: Digital business transformation is a complex process of changing business models, organizational structure, and enterprise management systems based on modern information technologies. With the accelerated development of the digital economy, enterprises are faced with the need to implement innovative solutions that improve the efficiency of production processes, optimize resource management, and enhance customer interactions. Modern technologies, including artificial intelligence, cloud computing, big data, the Internet of Things, blockchain technology, and robotic process automation, are becoming key tools for building organizations' competitive advantages.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: Digital transformation, information technology, digital economy, business process automation, artificial intelligence, big data, cloud computing, Internet of Things, digital management, enterprise competitiveness.
creator: Ulugbek Urunov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-31
publication date: 2026-05-31
starting page: 109
ending page: 121

GAMIFICATION IN DIGITAL MARKETING AS A TOOL FOR CONSUMER ENGAGEMENT
type: item
description: marketing tool for increasing consumer engagement and strengthening long-term brand loyalty. The author examines the concept's genesis, drawing on fundamental principles of behavioral psychology, motivation theory, and game design. The article provides a detailed analysis of key game elements, from rating systems and point accrual to multi-level quests and interactive loyalty programs. A significant portion of the study is devoted to the implementation of game mechanics in e-commerce, mobile services, and SMM, as well as the potential for synergy between gamification, Big Data, and neural networks. Finally, a methodology for evaluating the effectiveness of game strategies through conversion, retention, and financial return metrics is proposed. It is concluded that gamification is a strategic resource for achieving a competitive advantage in the modern digital environment.Scientific Novelty. The scientific novelty of this study lies in its comprehensive analysis of gamification as a digital marketing tool, taking into account current trends in digital business transformation. Key game mechanics are systematized, and their impact on consumer engagement in the digital environment is determined. A classification of key performance indicators for gamification is proposed, combining marketing, behavioral, and economic criteria. The role of artificial intelligence, big data analysis, and personalization in improving the effectiveness of game marketing strategies is substantiated, expanding existing scientific understanding of the application of gamification in modern digital communications. Purpose of the Study. The purpose of this study is to analyze the theoretical and practical aspects of gamification in digital marketing, identify its impact on consumer engagement, and evaluate the effectiveness of game mechanisms in increasing customer loyalty and marketing communications in the digital economy.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: Gamification, digital marketing, consumer engagement, user experience, game mechanics, loyalty programs, marketing communications, digital transformation, artificial intelligence, personalization, consumer behavior, e-commerce.
creator: Nataliia Butenko
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 55
ending page: 64

RAINY SEASON DISTRIBUTION OF HEAVY-METAL POLLUTION INDEX ALONG OKULU RIVERS IN ELEME LGA OF RIVERS STATE, NIGERIA
type: item
description: This study was conducted in order to determine the rainy season distribution of heavy metal pollution index (HPI) along Okulu rivers in Eleme local government area of Rivers State. Water samples were collected from distances of 100, 200, 300, 400 and 500m away from petrochemical effluent discharge point into the river using well-washed and rinsed bottles. Heavy metal contents of the water samples were analyzed specifically for cadmium, chromium, copper, lead, Iron, Nickel and Zinc. The heavy-metal pollution indices of the various samples were evaluated using the weighted average formula based on WHO and FME surface water standards. The results revealed that the HPI for the water samples at distances of 100, 200, 300, 400 and 500m away from effluent discharge point based on FME standards were 9771, 6325, 10681 and 5814 which indicated that the water samples were unfit for both domestic, Irrigation and industrial purposes while the HPI for the water samples at distances of 100, 200, 300, 400 and 500m away from effluent discharge point based on WHO standards were 35.06, 45,95, 95.30 109.87 and 205.43 which showed that water sample from distances of 100 and 200m away from discharge point are suitable for industrial and irrigation purposes but not for domestic purposes while water samples beyond 200m are not suitable for both domestic, industrial and irrigation purposes. The model of the distribution of the HPI along the sampled area revealed that there is non-linear sinusoidal relationship between HPI and distances along the sampled points. It was concluded that the river is highly polluted with heavy metals and the heavy metals are unevenly distributed along the river. It was recommended that communities along the Okulu rivers should not use the water from this river for both domestic, irrigation and industrial purposes due to high level of heavy-metal contents that could pose serious threat to their health.
subject: Articles
  topic: section
subject: Heavy-metals, Pollution Index, Rainy Season, Okulu River
  topic: keywords
creator: Osuji, F. C.
creator: Ugwoha, E.
creator: Yorkor, B.
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-07-31
publication date: 2026-07-31
starting page: 1
ending page: 12

SPECTRAL PROPERTIES OF SELF-ADJOINT PARTIAL INTEGRAL OPERATORS WITH KERNELS BELONGING TO A SPECIFIC FUNCTION CLASS
type: item
description: The study of partial integral operators has become one of the most significant directions in modern functional analysis due to its broad applications in mathematical physics, engineering, quantum mechanics, signal processing, and boundary value problems. Self-adjoint partial integral operators are of particular interest because their spectral characteristics possess remarkable mathematical properties that facilitate theoretical investigations and practical computations.
subject: Articles
  topic: section
subject: Partial integral operator, self-adjoint operator, Hilbert space, compact operator, spectrum, eigenvalue, kernel function, spectral decomposition, functional analysis.
  topic: keywords
creator: Hatamov Ma'ruf XXX
creator: Turopova Sohiba Djumanazarovna
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 179
ending page: 181

SPECTRAL PROPERTIES OF SELF-ADJOINT PARTIAL INTEGRAL OPERATORS WITH KERNELS BELONGING TO A SPECIFIC FUNCTION CLASS
type: item
description: Spectral theory has become one of the fundamental branches of functional analysis due to its wide range of applications in mathematics, physics, engineering, and computational sciences. The concept of spectrum provides valuable information about the behavior of linear operators and offers effective analytical tools for solving differential and integral equations.Among various classes of linear operators, self-adjoint operators occupy a central position because of their remarkable mathematical properties. Their spectra consist entirely of real numbers, and the associated eigenfunctions form orthogonal systems in Hilbert spaces. These characteristics simplify both theoretical investigations and numerical computations.Partial integral operators represent a natural generalization of classical integral operators and frequently appear in multidimensional mathematical models. They arise in the study of heat transfer, wave propagation, elasticity theory, quantum mechanics, image reconstruction, and stochastic processes. Their mathematical analysis requires a combination of operator theory, measure theory, and functional analysis.
subject: Articles
  topic: section
creator: Hatamov Ma'ruf XXX
creator: Turopova Sohiba Djumanazarovna
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 176
ending page: 178

ECONOMETRIC MODELING OF THE MAIN DETERMINANTS OF HOUSING PROVISION LEVEL
type: item
description: Housing provision is one of the most significant indicators of social welfare and sustainable economic development. This study investigates the major determinants influencing the level of housing provision using an econometric approach. Unlike traditional descriptive studies, this research applies multiple econometric techniques to examine the relationship between housing provision and socioeconomic factors such as household income, mortgage financing, construction investment, urbanization, demographic growth, employment, and inflation.
subject: Articles
  topic: section
subject: Housing provision, econometric modeling, housing market, multiple regression, mortgage finance, household income, construction investment, urbanization, demographic factors, economic development.
  topic: keywords
creator: Turopova Sohiba Djumanazarovna
creator: Hatamov Ma’ruf XXX
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 174
ending page: 175

ECONOMETRIC MODELING OF THE MAIN DETERMINANTS OF HOUSING PROVISION LEVEL
type: item
description: Housing is a fundamental human need and an essential component of economic and social development. It provides not only shelter but also contributes to health, education, labor productivity, and social welfare. The availability of adequate housing is often regarded as an indicator of national prosperity and institutional effectiveness. Countries with efficient housing markets generally experience stronger economic performance, greater social cohesion, and higher living standards.In recent decades, housing markets have undergone substantial transformations due to rapid urbanization, globalization, demographic changes, and technological development. Population growth has increased the demand for residential properties, while rising land prices and construction costs have limited the supply of affordable housing. These challenges are particularly evident in developing countries, where housing shortages continue to affect millions of households.
subject: Articles
  topic: section
creator: Turopova Sohiba Djumanazarovna
creator: Hatamov Ma'ruf XXX
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 171
ending page: 173

ADOPTION OF ARTIFICIAL INTELLIGENCE IN PREDICTIVE RISK ASSESSMENT IN SELECTED OIL AND GAS COMPANIES IN NIGERIA
type: item
description: This study examined the role of Artificial Intelligence adoption in predictive risk assessment within Nigerian oil and gas companies, focusing on its effectiveness in enhancing risk identification, evaluation, and management processes. A descriptive cross-sectional survey design was adopted, employing a proportionate sampling technique to select 256 participants from professionals and decision-makers involved in risk assessment, safety management, and operational roles across selected companies. A total of 256 questionnaires were distributed, out of which 249 were properly filled and valid for data analysis, representing a high response rate of 97.3%. Data was analyzed using the Statistical Package for the Social Sciences (SPSS) version 27.0. The results revealed that the adoption of AI technologies such as machine learning, predictive analytics, and data modelling has a significant positive impact on predictive risk assessment by increasing confidence in risk-mitigation strategies (Mean = 3.8), and management support for AI adoption (Mean = 3.8). This is followed by proactive incident prevention compared to traditional methods (Mean = 3.7), alignment of AI use with operational objectives (Mean = 3.7), and measurable improvements in safety outcomes (Mean = 3.7). AI-powered tools enabling quicker response to threats (Mean = 3.8), enhanced safety compliance (Mean = 3.8), tangible improvements in safety outcomes from AI investment (Mean = 3.8), and AI-based monitoring identifying risks before escalation (Mean = 3.8). The study concludes that AI plays a transformative role in improving predictive risk assessment and overall risk management effectiveness in the Nigerian oil and gas industry.
subject: Articles
  topic: section
subject: Artificial Intelligence, Predictive Risk Assessment, Oil and Gas Companies, Nigeria.
  topic: keywords
creator: Ayaraekpe, Mfonobong L.
creator: Avwiri. G. O.
creator: Ossia, C. V.
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 150
ending page: 170

MACHINE LEARNING-BASED DETECTION OF MALICIOUS WEB REQUESTS USING HTTP TRAFFIC FEATURES
type: item
description: Web applications have become essential components of modern digital infrastructure, supporting online banking, e-commerce, education platforms, healthcare systems and public administration services. However, their continuous exposure to the Internet makes them frequent targets of cyberattacks such as injection attacks, cross-site scripting, path traversal, authentication abuse and automated vulnerability scanning. Traditional rule-based security mechanisms remain useful for detecting known attack signatures, but they are often limited against modified, encoded or previously unseen malicious requests. This study investigates machine learning-based detection of malicious web requests using HTTP traffic features. The experiment uses the CSIC 2010 HTTP dataset, which contains normal and anomalous web requests generated for testing web attack protection systems. Nineteen request-level features were extracted from URL, request method and content fields, including URL length, character composition, encoded characters, path depth, request method indicators and content-related measures. Four machine learning models, namely Logistic Regression, Decision Tree, Random Forest and Linear Support Vector Machine, were trained and evaluated using accuracy, precision, recall, F1-score and confusion matrix analysis. The experimental results show that Random Forest achieved the best overall performance, with 92.27% accuracy, 92.47% precision, 88.37% recall and 90.37% F1-score. Feature importance analysis showed that URL length, URL letters, URL digits, content letters and content length were the most influential predictors. The findings indicate that machine learning can serve as an additional analytical layer for web application security, although its reliability depends on feature engineering, dataset representativeness, class balance and continuous monitoring.
subject: Articles
  topic: section
subject: Machine learning; web application security; malicious request detection; HTTP traffic; cybersecurity; anomaly detection; Random Forest; feature engineering.
  topic: keywords
creator: Sabina Norbekova Tolib qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 139
ending page: 149

EVALUATION OF THE EFFECTIVENESS OF STRENGTHENING BRICK MASONRY WITH GLASS-FIBER COMPOSITE REINFORCEMENT BASED ON EXPERIMENTAL TESTS
type: item
description: The article examines methods for strengthening brick masonry using composite materials. These methods have not become widespread in Uzbekistan because there is no regulatory framework governing their use. The article analyzes existing methods for reinforcing brick masonry and proposes a calculation methodology for these strengthening methods, with conclusions and recommendations based on the results. The aim of the study was to consider the technology and analyze the advantages and disadvantages of each method that should be used when selecting solutions for strengthening masonry. In conclusion, the need for further tests was confirmed in order to validate theoretical findings with practical results.
subject: Articles
  topic: section
subject: Masonry, stress state, elastoplastic body, moment, transverse force, reinforcement, cement mortars, masonry strength, calculation scheme.
  topic: keywords
creator: Z. A. Umirzakov
creator: A. Nazirov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-31
publication date: 2026-05-31
starting page: 103
ending page: 108

REGENERATION EFFICIENCY AND LONG-TERM STABILITY OF FE-MOFS FOR REPEATED NUTRIENT ADSORPTION CYCLES
type: item
description: The sustainability and practical implementation of metal–organic frameworks (MOFs) for water treatment depend largely on their regeneration efficiency, structural stability, and adsorption reusability under repeated operational cycles. This study evaluates the regeneration performance and long-term adsorption stability of an iron-based metal–organic framework (Fe-MOF), Fe-UPH.COHSE–NH₂, for repeated phosphate and nitrate removal from aqueous solutions. The experiments concerning the nutrient recovery and reusability of the adsorbent have been done using batch adsorption-desorption process using diluted sodium hydroxide as the regenerating agent. Methods such as adsorption capacity test, kinetics modeling, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), BET surface area analysis, scanning electron microscopy (SEM), and thermogravimetric analysis (TGA) have been employed to monitor the adsorption capacity, structural stability, and physicochemical stability. The regenerated Fe-MOF after several adsorption-desorption cycles retains its high phosphate removal efficiency (>85%) indicating high structural stability and regeneration ability. Phosphate adsorption remained predominantly governed by chemisorption and inner-sphere complexation, while nitrate adsorption exhibited comparatively weaker retention due to electrostatic interaction mechanisms. It was discovered that partial pore clogging, active site saturation, and minimal framework distortion were responsible for the small decreases in adsorption capability after successive regeneration processes. The adsorbent recovered from successive regeneration processes retained its heterogeneous active sites and favorable adsorption thermodynamics as revealed by the kinetic and isotherm studies. Finally, it can be stated that the findings indicate that Fe-UPH.COHSE-NH₂ is a sustainable adsorbent with high regeneration capability and stability, which makes it an excellent candidate for nutrient remova…
subject: Articles
  topic: section
subject: Fe-MOF; adsorption regeneration; phosphate removal; nitrate removal; adsorption stability; nutrient remediation; reusable adsorbent; wastewater treatment.
  topic: keywords
creator: Umoh, Enobong T.
creator: Udeh, Ngozi U.
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 125
ending page: 138

INTELLIGENT ALGORITHMS FOR PERSONALIZED TRAVEL ROUTE PLANNING A GRAPH NEURAL NETWORK AND HYBRID MOVNS-A* APPROACH
type: item
description: Personalized travel route planning is a combinatorial optimization problem that must simultaneously satisfy diverse user preferences, budget constraints, time limitations, and geographic factors. Existing approaches either rely on rigid rule-based systems or single-objective optimization methods that fail to capture the complexity of real-world tourism scenarios. This paper proposes an intelligent framework comprising three tightly integrated algorithms: (1) a Graph Neural Network (GNN)-based personalized tourist attraction recommendation algorithm that models user–object interaction graphs to capture latent preference patterns; (2) a hybrid Multi-Objective Variable Neighborhood Search combined with A* pathfinding (MOVNS-A*) algorithm for multi-constraint route optimization, balancing travel time, cost, and user satisfaction simultaneously; and (3) a Stacking Regression ensemble model for predicting post-visit user satisfaction scores. Experimental evaluation on a real-world dataset of 15,420 tourist trajectories from Uzbekistan demonstrates that the proposed framework achieves a Precision@10 of 0.847, an NDCG@10 of 0.831, and a mean route satisfaction prediction error (RMSE) of 0.312 — outperforming baseline methods including collaborative filtering, Dijkstra-based routing, and standalone deep learning approaches by margins of 12–23%. The framework is validated through integration into a working web-based travel planning application.
subject: Articles
  topic: section
subject: Personalized route planning; graph neural networks; multi-objective optimization; MOVNS-A* algorithm; travel recommendation system; stacking regression; tourist itinerary.
  topic: keywords
creator: Gozal Absalamova
creator: Akmal Abdumalikov
creator: Muxlisa Olimova
creator: Shuxrat Kamalov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 115
ending page: 124

FORMATION OF INFORMATION MODELING COMPETENCE IN THE PROCESS OF PHYSICS EDUCATION
type: item
description: The rapid development of information and communication technologies has significantly transformed educational practices, particularly in science education. One of the essential competencies required in modern education is information modeling competence, which enables learners to represent, analyze, and interpret physical phenomena through various models. This article examines the formation of information modeling competence in the process of physics education. The study explores theoretical foundations, pedagogical approaches, and digital technologies that support the development of modeling skills among students. Special attention is given to computer simulations, virtual laboratories, mathematical modeling, and problem-based learning as effective tools for enhancing students’ understanding of physical concepts.
subject: Articles
  topic: section
subject: Information modeling, physics education, modeling competence, digital technologies, computer simulation, scientific literacy, problem-based learning.
  topic: keywords
creator: Qurbonova Nafisa Ilhom qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 110
ending page: 114

THE ROLE OF ARTIFICIAL INTELLIGENCE IN IMPROVING CARDIOVASCULAR FUNCTION
type: item
description: This article analyzes the role and importance of artificial intelligence (AI) in improving the functioning of the cardiovascular system. It highlights the application of AI technologies in the field of cardiology, particularly in early disease detection, accurate diagnosis, real-time monitoring, and the development of personalized treatment strategies. Furthermore, the study examines how AI can process large volumes of medical data and predict the risk of cardiovascular diseases, thereby enhancing the effectiveness of preventive measures. The article also discusses the role of AI-based systems in improving the quality of healthcare, along with the challenges associated with their implementation, including data security, privacy, regulatory compliance, and the need for specialized training of medical professionals.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: Artificial intelligence (AI), cardiology, cardiovascular diseases, early diagnosis, medical imaging, predictive models, cardiac monitoring, wearable devices, personalized treatment, healthcare technologies, data analysis, prevention, digital medicine.
creator: Daminova Barno Esanovna
creator: Xolmurodova Asila Normurod qizi
creator: Xukumova Durdona Akmal qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 105
ending page: 109

INTEGRATION OF DISCIPLINES IN TEACHING CHEMICAL BONDING AND VALENCE IN ATOMIC PHYSICS
type: item
description: The interdisciplinary integration of scientific subjects has become an important approach in modern education, enabling students to develop a holistic understanding of natural phenomena. This article examines the integration of physics and chemistry in teaching chemical bonding and valence within the context of atomic physics. The study explores how concepts of atomic structure, electron configuration, quantum mechanics, and electromagnetic interactions provide a physical basis for understanding chemical bonds and valence. Particular attention is given to interdisciplinary teaching methods that connect theoretical knowledge from physics and chemistry, promoting deeper conceptual understanding and scientific literacy.
subject: Articles
  topic: section
subject: Interdisciplinary integration, atomic physics, chemical bonding, valence, science education, quantum mechanics, electron configuration, scientific literacy.
  topic: keywords
creator: Khojamberdiyeva Jamila Norkobilovna
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 100
ending page: 104

NEGATIVE AND POSITIVE EFFECTS OF USING AN ELECTRONIC DIGITAL SIGNATURE
type: item
description: This article analyzes the role of electronic digital signature (EDS) technology in the modern process of information exchange, as well as its legal, economic, and technical aspects. The research highlights the positive impacts of EDS, such as the acceleration of document workflow, ensuring confidentiality, and the efficiency of remote services. At the same time, negative consequences associated with the use of EDS, including the risks of cyberattacks, theft of private keys, and dependence on technical infrastructure, are systematically demonstrated. The article concludes with practical recommendations for enhancing system security.
subject: Articles
  topic: section
subject: Electronic digital signature, information security, cryptography, electronic document management, cybersecurity, remote authentication, identification, digital economy.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Razzoqov Mustafo Matniyoz o`g`li
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-08
publication date: 2026-06-08
starting page: 94
ending page: 99

USE OF ARTIFICIAL INTELLIGENCE IN THE DEVELOPMENT OF AUTOMATED INFORMATION SYSTEMS
type: item
description: This article examines the theoretical and practical aspects of applying artificial intelligence (AI) technologies in the creation of modern automated information systems (AIS). It analyzes the impact of AI algorithms on data processing speed, decision-making accuracy, and the adaptive characteristics of these systems.
subject: Articles
  topic: section
subject: Artificial intelligence, automated systems, machine learning, neural networks, Big Data, cybersecurity, digital economy.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Yusufova Asila Nabi qizi
creator: Dustmurodova Ruxshona Yodgor qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-08
publication date: 2026-06-08
starting page: 90
ending page: 93

DEVELOPING PRACTICAL COMPETENCE IN PHYSICS LABORATORY INSTRUCTION THROUGH MULTIFUNCTIONAL PROFESSIONALLY ORIENTED TASKS: A COMPETENCY-BASED DIDACTIC MODEL
type: item
description: This article presents a scientifically enriched and methodologically updated model for developing students' practical competence in physics laboratory instruction through a system of multifunctional professionally oriented tasks. The study reinterprets the physics laboratory not as a procedural space where students mechanically reproduce a prescribed experiment, but as a competence-forming learning environment in which theoretical knowledge, measurement culture, data analysis, professional reasoning, evidence-based conclusion-making and reflective self-assessment are integrated into a single didactic cycle. The proposed approach structures laboratory work through preparation, admission to the experiment, experimental performance, data processing, defense of results and reflection. Multifunctional tasks are designed to activate conceptual understanding, practical application, analytical comparison, modelling, evaluation and transfer of knowledge to engineering contexts. The article substantiates the pedagogical value of professionally oriented tasks in connecting physics concepts with real technical situations, improving students' autonomy, and strengthening the methodological culture of laboratory learning. A competency-based didactic model, assessment evidence, and a pedagogical-didactic matrix are proposed for implementation in technical higher education institutions.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: Physics laboratory instruction; practical competence; professionally oriented tasks; multifunctional tasks; competency-based education; didactic support; experimental learning; reflective assessment; engineering thinking; evidence-based learning.
creator: Ergash Binoqulovich Maxmanov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-09
publication date: 2026-06-09
starting page: 82
ending page: 89

THE ROLE OF TET2 MUTATIONS IN THE DEVELOPMENT OF CHIP-ASSOCIATED ATHEROSCLEROSIS
type: item
description: TET2 (Ten-Eleven Translocation 2) mutations are among the most common in CHIP (Clonal Hematopoiesis of Indeterminate Potential) and the most clinically significant in cardiology. Loss of TET2 function leads to hyperactivation of the NLRP3 (NOD-like receptor family pyrin domain containing protein 3) inflammasome in macrophages and overproduction of the interleukins IL-1β, IL-6, and TNF-α, which causes chronic vascular inflammation. This inflammation contributes to endothelial dysfunction, the formation of unstable atherosclerotic plaques, and increases the risk of myocardial infarction and stroke by 2–4 times. Given these findings, it is suggested that CHIP can be considered a new independent risk factor for atherosclerosis, and patients with TET2-mutant CHIP may be the best candidates for therapy with IL-1β inhibitors.
subject: Articles
  topic: section
subject: CHIP, TET2, NLRP3 inflammasome, myocardial infarction, atherosclerosis, cardiovascular disease.
  topic: keywords
creator: Gaziyeva Anastasiya Ruslanovna
creator: Matkarimova Dilfuza Saburovna
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-06
publication date: 2026-06-06
starting page: 74
ending page: 81

INFORMATION AND LEGAL RELATIONS OF THE E-STATE IN THE CONCEPT OF E-GOVERNMENT
type: item
description: This article analyzes the essence, structure and features of the information and legal relations that arise within the framework of the concept of e-government. In the E-state system, the legal basis of information exchange, the mechanisms of digital interaction between state bodies, citizens and economic entities are considered. The state and improvement directions of the regulatory framework regulating information security, protection of personal data and the activities of State Information Systems are established.
subject: Articles
  topic: section
subject: e-Government, E-State, Information and legal relations, digital transformation, information security, personal data, public services, digital law.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Eshtemirova Sabrina Bahrom qizi
creator: Yo’ldosheva Gulsevar Axrorjan qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-06
publication date: 2026-06-06
starting page: 67
ending page: 73

SCHEMATIC ORGANIZATION OF THE SCIENTIFIC POTENTIAL OF PROFESSORS AND TEACHERS THROUGH TALENTED STUDENTS
type: item
description: This article will consider the issues of schematic Organization of the scientific potential of gifted students and professors in higher education institutions as an interconnected system. The concept of a gifted student, its role in scientific activity and its interaction with the scientific potential of a professor are analyzed. Organizational schemes, models and mechanisms are proposed that serve to develop scientific potential. In the higher education system of Uzbekistan, effective ways of organizing scientific potential through talented students are based.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: Talented student, scientific potential, faculty, research activities, mentor-mentee relations, schematic organization, intellectual capital, Scientific School, student scientific circle, multi-level cooperation model.
creator: Daminova Barno Esanovna
creator: Yunusova Zaxro Zafarjon qi
creator: Sattarova Sevinch Jovli qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-06
publication date: 2026-06-06
starting page: 60
ending page: 66

DEVELOPING MECHANISMS FOR DEVELOPING THE TOURISM INDUSTRY BASED ON ARTIFICIAL INTELLIGENCE
type: item
description: This article examines the mechanisms for developing the tourism sector based on artificial intelligence technologies. It highlights the role of artificial intelligence in tourism systems, particularly in data analysis, the provision of personalized services, and the improvement of service quality through chatbots and intelligent recommendation systems. The study also emphasizes the importance of artificial intelligence in effective tourism management, forecasting tourist flows, and the rational use of resources. In addition to outlining the advantages of implementing these technologies, the article analyzes existing challenges and explores the prospects for the application of artificial intelligence in the tourism industry of Uzbekistan.
subject: Articles
  topic: section
subject: Artificial intelligence, tourism, digital technologies, intelligent systems, chatbots, recommendation systems, data analysis, forecasting, personalized services, tourism management.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Xudoyberdiyeva Zulfiya
creator: Jontemirova Husnora
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-06
publication date: 2026-06-06
starting page: 56
ending page: 59

METHODOLOGY FOR DEVELOPING PRACTICAL COMPETENCIES OF STUDENTS IN TEACHING THE DISCIPLINE "COMPUTER NETWORKS" BASED ON THE INTEGRATION OF GENERATIVE ARTIFICIAL INTELLIGENCE AND CISCO PACKET TRACER
type: item
description: Today, the use of digital educational technologies and tools in the higher education system is one of the main means of improving learning efficiency. This article proposes a methodology for developing students' practical competencies based on the integration of generative artificial intelligence tools and the Cisco Packet Tracer software environment in teaching the discipline "Computer Networks." The article analyzes the capabilities of modern digital educational technologies. Mechanisms have been developed for forming individual assignments during the lesson using generative AI, automatic analysis of network configurations, and conducting practical laboratory classes. The experimental results showed that the proposed methodology significantly improves students' practical skills, develops their ability to work independently, and enhances their competencies in configuring network devices.
subject: Articles
  topic: section
subject: Generative AI, Cisco Packet Tracer, network devices, virtual laboratory, AI-assisted learning, digital education system.
  topic: keywords
creator: Turdiyeva Gavhar Saidovna
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-06
publication date: 2026-06-06
starting page: 51
ending page: 55

PREPARATION OF MODERN PRESENTATIONS IN THE EDUCATIONAL PROCESS, OPPORTUNITIES AND PRACTICAL APPROACHES
type: item
description: This article examines the theoretical foundations and practical significance of preparing modern presentations in the educational process. The impact of multimedia presentations on the quality of education is analyzed, and the possibilities of creating an interactive and visual learning environment using various digital tools are explored. During the research, a survey was conducted among students and teachers, and a comparative analysis of the effectiveness of modern presentation software (Microsoft PowerPoint, Canva, Prezi, Google Slides), was carried out. The article provides practical recommendations on design principles, data visualization methods, and improving pedagogical competence in the preparation of presentations.
subject: Articles
  topic: section
subject: Modern presentation, multimedia education, visualization, digital pedagogy, presentation tools, educational technologies, interactive learning, Canva, PowerPoint, Prezi.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Mahmudov Muhammad Botir oʻgʻli
creator: Xasanov Shavkat Abduraxim o‘g‘li
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-06
publication date: 2026-06-06
starting page: 45
ending page: 50

MODERN TYPES OF DATABASE MANAGEMENT SYSTEMS AND THEIR CAPABILITIES
type: item
description: This article analyzes the modern types of database management systems (DBMS), their architectures and core capabilities. Various paradigms such as relational, NoSQL, NewSQL, graph-oriented, object-oriented and time-series databases are comparatively examined. The strengths, application domains, and limitations of each type are described. Contemporary trends including cloud computing integration, distributed architecture, and artificial intelligence embedding are also discussed. The research findings can serve as a practical guide for database architects and software engineers in selecting the optimal DBMS.
subject: Articles
  topic: section
subject: Database management system, relational DBMS, NoSQL, NewSQL, graph database, distributed systems, cloud computing, CAP theorem, sharding, replication.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Nuraliyeva Madina
creator: Eshmirzayeva Lobar
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-05
publication date: 2026-06-05
starting page: 38
ending page: 44

METHODS FOR SOLVING ECONOMIC PROBLEMS USING ARTIFICIAL INTELLIGENCE
type: item
description: This article analyzes methods for solving economic problems using artificial intelligence technologies. In particular, important areas such as economic forecasting, reducing production costs, risk management in the banking and financial system, determining market demand, and analyzing the labor market are highlighted. The article describes in a scientific manner the role of artificial intelligence in the modern economy, its practical significance, and its role in increasing economic efficiency.
subject: Articles
  topic: section
subject: Artificial intelligence, economics, economic forecasting, market analysis, banking system, digital economy, labor market.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Ziyodullayeva Musharraf Rustam qizi
creator: Ziyodullayeva Gulsanam Ilhom qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-05
publication date: 2026-06-05
starting page: 33
ending page: 37

DATABASE MODELS AND THE ENTITY-RELATIONSHIP MODEL
type: item
description: This article analyzes the types of data models that form the basis of database management systems (DBMSs) and their principles of operation. In particular, the components of the Entity-Relationship (ER) model, which is the first and most important stage of database design, the attribute hierarchy and logical relationships between objects are discussed in detail. The article shows the importance of models in reducing errors and ensuring data integrity during the design process.
subject: Articles
  topic: section
subject: Database, Relational model, ER-model, Entity, Attribute, Relationship, SQL, Data hierarchy, Database design.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Qahramonova Mushtariybonu Abdurahmon qizi
creator: Rashidova Sevinch Nurbek qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-05
publication date: 2026-06-05
starting page: 28
ending page: 32

METHODS AND APPLICATIONS OF USING ARTIFICIAL INTELLIGENCE IN SOLVING PROBLEMS OF THE DIGITAL ECONOMY
type: item
description: This article will study the theoretical foundations, practical methods and areas of application of the use of artificial intelligence technologies in solving current problems in the field of digital economics. The application of artificial intelligence is analyzed in the areas of financial analysis, trade, production, agriculture and public administration. In Uzbekistan's digital economy, artificial intelligence opportunities and application barriers are assessed. Practical recommendations for accelerating national digital transformation will be developed.
subject: Articles
  topic: section
subject: Artificial intelligence, digital economy, machine learning, natural language processing, big data, neural networks, digital transformation, economic forecasting, automation.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Xurramova Zamira Abdirahmat qizi
creator: Tirkashova Dilshoda Dilmurod qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-05
publication date: 2026-06-05
starting page: 22
ending page: 27

INFORMATION SYSTEMS AND SOFTWARE IN DATABASE CREATION
type: item
description: This work analyzes the theoretical and practical foundations of database formation, the structure of information systems, and the modern software used to manage them. The role of relational and non-relational databases in the processes of systematizing, storing, and processing data is highlighted, along with issues of enhancing the security and efficiency of information systems. The research results include recommendations for the correct selection of software solutions in database design.
subject: Articles
  topic: section
subject: Database, information systems, software, DBMS (Database Management Systems), SQL, NoSQL, data architecture, design.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Po‘latova Parizoda Farrux qizi
creator: Meyliyeva Sevinch Davlatbek qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-05
publication date: 2026-06-05
starting page: 17
ending page: 21

DATABASE MANAGEMENT AND ANALYSIS WITH THE HELP OF ARTIFICIAL INTELLIGENCE
type: item
description: This article discusses in detail the role of artificial intelligence technologies in database management and data analysis. In modern information systems, the processes of storing, processing, and efficiently using large volumes of data are becoming increasingly complex, making the use of artificial intelligence highly important. The article explains the concept of databases, their main functions, and database management systems, while also analyzing major areas of artificial intelligence such as machine learning, neural networks, and expert systems. In addition, the possibilities of automatic database optimization, rapid data processing, error detection, security enhancement, forecasting, and effective analysis of large-scale data using artificial intelligence are examined.
subject: Articles
  topic: section
subject: Artificial intelligence, database, data management, data storage, data processing, data analysis, information systems, machine learning, neural networks.
  topic: keywords
creator: Daminova Barno Esanovna
creator: Toshmurodova Rohat Tojiboy qizi
creator: Rustamova Shahlo Rustam qizi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc/4.0
date: 2026-06-05
publication date: 2026-06-05
starting page: 12
ending page: 16