Innovative: International Multidisciplinary Journal of Applied Technology (2995-486X)
Innovative: International Multidisciplinary Journal of Applied Technology (IMJAT) with U.S ISSN 2995-486X is a peer-reviewed, open-access scientific journal dedicated to publishing original research and innovative developments across a broad spectrum of applied and technical sciences. With its growing reputation, IMJAT continues to be a valuable platform for academics, researchers, engineers, and industry professionals seeking to publish impactful research that advances applied science and technology on a global scale. We are pleased to announce that IMJAT has been officially recognized by the Higher Attestation Commission (OAK) of the Republic of Uzbekistan for meeting the criteria required for technical sciences publications. As per OAK Decision No. 368/4 dated March 6, 2025, the journal is now listed as a recommended scientific publication for “05.00.00 – Technical Sciences, making it a valid outlet for PhD and DSc researchers to publish their dissertation-related scientific results. JOURNAL INFORMATION Journal title : Innovative: International Multidisciplinary Journal of Applied Technology (IMJAT) Initials : Innovative Abbreviation : Int.Multi.Jour. Applied. Techno. Frequency : Monthly Published DOI : Publisher Association : Antis Publishing House Online ISSN : ISSN 2995-486X (Online) | Innovative | The ISSN Portal Collaboration Institution : Kokand State University Publisher : Multi Journals Press Citation Analysis : IEEE Reference Style Accreditation : - Abstracting and Indexing : Click here
COMPARATIVE ANALYSIS OF METHODS FOR INCREASING THE CAPACITY OF FIBER-OPTIC COMMUNICATION LINES AND EVALUATION OF A SINGLE-FIBER TRANSMISSION METHOD USING Y-SPLITTERS
The continuous growth of broadband traffic and the limited availability of optical fibers in existing fiber-optic communication networks require the development of cost-effective methods for increasing transmission capacity. This paper presents a comparative analysis of conventional approaches, including deployment of new fiber-optic communication lines, wavelength-division multiplexing (WDM), and transmission rate enhancement, together with a proposed method based on converting dual-fiber optical transmission systems into a single-fiber mode using passive optical Y-splitters. A mathematical model based on signal-to-noise ratio (SNR), bit error rate (BER), and optical power budget analysis is developed. The obtained results demonstrate that the proposed method increases effective fiber utilization by 1.8–2 times while maintaining transmission quality within standardized limits. The approach is particularly suitable for rural and regional communication networks characterized by limited budgets and a shortage of available optical fibers.
Copyright (c) 2026 Kiyamov Rakhmatullo Ruziyevich (Author)
DESIGNING MODERN CLOTHING USING LOCAL TEXTILE MATERIALS BASED ON SUSTAINABLE DEVELOPMENT PRINCIPLES
This article investigates the design of modern garments using local textile materials based on sustainable development principles. The ecological, economic, and aesthetic advantages of locally produced fabrics were analyzed, and their potential application in contemporary fashion design was evaluated. The study proposes environmentally friendly design approaches that integrate national textile traditions with modern fashion requirements. The results demonstrate that the use of local materials contributes to sustainable production, cultural preservation, and increased competitiveness in the light industry sector.
Copyright (c) 2026 Mamatkulova Kunduzkhon Umarovna, Resi Sepsilia Elvera (Author)
Artificial Intelligence-Driven Cyber Threat Detection for Protecting Critical Digital Infrastructure
Background: Energy grids and healthcare systems and financial networks and transportation systems more vulnerable to sophisticated cyber threats. The signature-based detection systems which rule-based cybersecurity methods use no longer provide sufficient protection against advanced persistent threats and zero-day exploits and AI-driven cyberattacks. Methods: We conducted their investigation through a data-based system which used simulated data that demonstrated actual conditions of essential infrastructure systems which included energy and healthcare and financial institutions. The dataset includes 500 entries which contain network traffic information and system operation patterns and transaction data elements that show both regular and harmful system activities. Random Forest and Gradient Boosting and Long Short-Term Memory (LSTM) and Auto encoder models through their performance on accuracy and precision and recall and F1-score and detection latency and error rates. Result: This finding demonstrate that AI-powered systems deliver better results than conventional methods because they produce accuracy percentages which range from 92% to 97%. Auto encoder model which uses deep learning techniques achieved the best results with 96.7% accuracy and maintained a false positive rate of 3.5%. The system achieved threat detection times which dropped by more than 90% to provide organizations with the ability to detect threats in real time. Conclusion: The models demonstrated outstanding performance when they needed to identify complex cyber threats included advanced persistent threats and zero-day attacks.
Copyright (c) 2023 Chowdhury Amin Abdullah, Md Jahidul Islam Ridoy (Author)
FORECASTING ROAD TRAFFIC CAPACITY USING MATHEMATICAL MODELING OF TRAFFIC FLOW DYNAMICS
The rapid growth of urbanization, motorization, and transportation demand has significantly increased the complexity of traffic management in modern cities. Accurate forecasting of road traffic capacity has therefore become a crucial task for transportation engineers, urban planners, and policymakers seeking to improve mobility, reduce congestion, and optimize infrastructure utilization. This study presents a mathematical modeling framework for predicting road traffic capacity based on fundamental traffic flow dynamics. The proposed approach employs the classical relationship between traffic flow, traffic density, and average vehicle speed and integrates an exponential speed–density function to describe nonlinear traffic behavior under varying congestion conditions. The mathematical model enables the determination of critical traffic density and maximum traffic throughput through analytical optimization of the flow–density relationship. Numerical simulations were conducted using a wide range of traffic density values to evaluate the model’s predictive performance and investigate congestion formation mechanisms. The simulation results demonstrate that traffic flow increases with density up to a critical threshold, beyond which traffic instability and congestion effects emerge, causing a reduction in operational efficiency. Furthermore, the model successfully reproduces the nonlinear characteristics of real traffic systems and provides physically interpretable estimates of roadway capacity. The findings indicate that the proposed modeling approach can serve as an effective tool for short-term and medium-term traffic forecasting, transportation planning, and intelligent transportation system applications. The model is computationally efficient, analytically transparent, and easily adaptable to various road network conditions. In addition, the framework creates opportunities for integration with real-time traffic monitoring technologies, sensor networks, and artificial intelligence algorithms. The proposed methodology contributes to the advancement of data-driven traffic management strategies and provides a practical foundation for improving road network performance, reducing congestion, and supporting sustainable urban transportation development.
Intelligent Transportation Systems (ITS)
Copyright (c) 2026 Mamadaliev Foziljon Abdullaevich (Author)
CONSUMER-ORIENTED DESIGN STRATEGIES FOR MODERN LIGHT INDUSTRY PRODUCTS
This article discusses the importance of consumer-oriented design strategies in the development of modern light industry products. The study analyzes the main factors influencing the creation of competitive products, including consumer needs, ergonomic indicators, aesthetic requirements, and functional characteristics. Special attention is paid to the use of digital technologies, innovative design methods, and sustainable development principles in the product development process. The research results show that a deep analysis of consumer requirements contributes to improving product quality, expanding market opportunities, and strengthening the competitiveness of light industry enterprises. A consumer-oriented approach enables the creation of modern, comfortable, and highly demanded products that meet the requirements of a rapidly developing market. The findings indicate that the implementation of consumer-oriented design strategies serves as a critical factor in improving product innovation, increasing market adaptability, and ensuring sustainable growth within the light industry sector. Consequently, the research provides valuable theoretical and practical insights for designers, manufacturers, and industry stakeholders seeking to develop products that effectively respond to evolving consumer demands.
Copyright (c) 2026 Innovative: International Multidisciplinary Journal of Applied Technology https://creativecommons.org/licenses/by/4.0
Leveraging Strategic Management Information Systems for Organizational Resilience: Integrating Artificial Intelligence, Financial Risk Mitigation, and Sustainable Marketing
Strategic Management Information Systems (SMIS) have emerged as critical tools for enhancing organizational resilience in an increasingly dynamic, technology-driven, and uncertain business environment. This study examines the integration of artificial intelligence (AI), financial risk mitigation strategies, and sustainable marketing practices within SMIS to strengthen organizational performance and long-term sustainability. The review highlights the role of SMIS in supporting strategic decision-making, resource optimization, risk assessment, and organizational adaptability through the effective management and analysis of information. The integration of enterprise systems such as Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), and Risk Management Information Systems (RMIS) enables organizations to develop a comprehensive understanding of operational performance and potential risks. Artificial intelligence significantly enhances SMIS by improving data management, predictive analytics, decision support, and operational automation. AI-driven technologies facilitate real-time analysis of large datasets, enabling organizations to forecast trends, identify emerging risks, and optimize business processes. Predictive analytics further strengthens financial risk mitigation by providing proactive insights into market volatility, credit risk, and operational uncertainties. The study also emphasizes the growing importance of sustainable marketing, where AI supports environmentally responsible business practices through customer behavior analysis, personalized marketing, resource optimization, and supply chain efficiency. Organizational resilience is reinforced through effective leadership, governance, knowledge sharing, continuous learning, and strategic alignment. These factors enable organizations to anticipate, adapt to, and recover from disruptions while maintaining competitive advantage. The findings suggest that organizations adopting these integrated approaches are better positioned to navigate uncertainty and achieve long-term success in a rapidly evolving global marketplace.
Strategic Management Information Systems (SMIS)
Copyright (c) 2025 Md. Nazmul Haque, Md. Sohel Masud (Author)
Course Equations for Studying The Stability and Controllability of Wheeled Machines
The controllability and stability of self-propelled energy vehicles are key parameters that determine their effectiveness in agricultural production and safety during transportation work. This work examines the course equations of wheeled machines used to analyze their stability and controllability. The influence of steering, the features of hydraulic steering systems, and their influence on the dynamic characteristics of machines are being investigated. Mathematical models are presented that take into account the rolling angles of the wheels, the transverse tilt of the machine frame, and the correction factors reflecting the influence of external factors on the stability of the movement. The obtained results can be used to optimize the structural parameters of steering and improve the safety of wheeled vehicles during their operation on public roads.
Copyright (c) 2025 Tursunov Ibragim Samandarovich, Ibragimov Botir Dastamovich (Author)
Numerical Solution of a Nonlinear Fractional Diffusion Problem
This article constructs a numerical solution for a nonlinear diffusion equation with a time-fractional derivative. The considered problem is posed on a semi-infinite domain, where the diffusion coefficient is expressed through a power function of the solution. The boundary condition of the problem also has a nonlinear form. The time-fractional derivative is discretized by an L1-type fractional difference approximation, while the spatial operator is discretized by the finite difference method in conservative form. The nonlinear diffusion coefficient is taken from the previous time layer, leading to a semi-implicit scheme. As a result, a tridiagonal system of linear algebraic equations is obtained at each time layer. This approach simplifies the computational process, improves stability, and provides a convenient framework for practical implementation.
Copyright (c) 2026 Xolmurzayeva Nigora Abdumurotovna (Author)
MECHATRONIC CONTROL ALGORITHM FOR AN AUTOMOTIVE COOLING SYSTEM FAN
This paper investigates a mechatronic control algorithm aimed at improving the operational efficiency and optimizing the energy consumption of a passenger car cooling system fan. The negative impacts of the conventional ON/OFF (switching) method on system stability, electrical grid current surges, and the mechanical durability of motors are analyzed. To simultaneously ensure the operational economy and thermal stability of the system, an adaptive mechatronic control algorithm is considered, which modifies control parameters in accordance with the current operating modes of the engine. In the proposed mechatronic system, the fan voltage and rotation speed are controlled in a stepped and smooth manner according to temperature variations. The advantages of the proposed algorithm are evaluated for high ambient temperatures and heavy urban traffic conditions. The results indicate that mechatronic control allows for reducing mechanical loads on fan motors, saving electrical energy, and maintaining the engine temperature stably within the optimal operational range.
Copyright (c) 2026 A.I. Yangibayev, F.SH. Umerov (Author)
THE IMPACT OF INTEGRATING LEAN MANUFACTURING AND QUALITY MANAGEMENT SYSTEMS ON ENTERPRISE EFFICIENCY
This article investigates the implementation of a quality management system based on lean production principles and the assessment of its effectiveness. The study analyzes approaches aimed at reducing losses in production processes, ensuring efficient use of resources, and continuously improving quality. In particular, production processes were optimized based on 5S, Kaizen, value stream analysis, and standardized work methods. The results showed that integrating lean production elements with the quality management system helps reduce defect levels, decrease production costs, and improve management efficiency in enterprises.
Copyright (c) 2026 Boykishiyeva Dilnozakhon Abdusalomovna (Author)
MATHEMATICAL ANALYSIS OF THE R-PARAMETRIC OPERATION PRESENTED IN THE O'ZMST 286:2024 STANDARD
This article mathematically analyzes the R parametric multiplication operation introduced in the national standard of the Republic of Uzbekistan O'zMSt 286:2024 "Processes of generating and verifying electronic digital signatures". The theoretical foundations of the parametric multiplication and exponentiation operations presented in the standard are considered, and the computational processes generated on the basis of these operations are analyzed using examples. In particular, the commutativity of the parametric multiplication operation, the determination of the inverse element, and the exponentiation processes are mathematically considered. Additionally, the computational efficiency of the method recommended in the standard is analyzed during the calculation of large powers, and the possibility of optimizing this calculation is demonstrated. The research results determine that certain computational processes related to the R-parametric operation can be simplified.
Copyright (c) 2026 N. R. Zaynalov, U. B. Sharipova, B. Sh. Ibrohimov, O. A. Oydinov (Author)
MORPHOLOGICAL CHARACTERIZATION BY SCANNING ELECTRON MICROSCOPY (SEM) OF COMPOSITE ADSORBENTS DERIVED FROM PLANT HUSK WASTE: A BASIS FOR DEVELOPING ECO-FRIENDLY MATERIALS FOR POLLUTANT ADSORPTION
This study investigates the morphological features, obtained by scanning electron microscopy (SEM), of individual activated carbons prepared from agricultural and fruit-processing wastes apricot stone shells, walnut shells and grape seed shells and of their three-component composite adsorbent. The samples were pyrolysed at 600 °C in an inert atmosphere, chemically activated with KOH, and converted into a composite by mechanical mixing in an equal mass ratio (1:1:1) followed by a secondary heat treatment (300 °C). SEM analysis revealed that each precursor forms a distinct carbon skeleton: the apricot pyrolysate showed an open cellular (honeycomb-like) structure (cell density 400–600 cells/mm²), the walnut pyrolysate a dense sponge-like 3D-interconnected structure (800–1000 cells/mm²), and the grape pyrolysate a lamellar (plate-like) and “Swiss-cheese” morphology. KOH activation opened the cell walls in all samples and generated submicron pores (200–500 nm). The composite developed a hybrid “cheese–cellular–plate” morphology, absent in any individual component, together with a zone rich in uniformly sized (1–2 µm) circular pores, which morphologically confirms the synergistic effect of compositing. The resulting granular commercial form (0.3–0.8 mm) indicates the potential of the composite for industrial-scale application.
Copyright (c) 2025 Karimova Zarifa, Nurmurodov Tulqin (Author)
PHYSICO-CHEMICAL, TEXTURAL AND OPERATIONAL PROPERTIES OF CATALYSTS OBTAINED FROM LOCAL MINERAL RAW MATERIALS AND INDUSTRIAL TECHNOGENIC WASTE
The physico-chemical, textural, mechanical and operational properties of catalysts prepared from local mineral raw materials Oltintog’ and Angren kaolins, various grades of Navbahor bentonite, and Karmana opaque zeolite-bearing rocks together with industrial technogenic waste (metal-oxide active components) were studied. The supports were modified thermally, by acid treatment and hydrothermally; CuO, Bi2O3, NiO, CoO, ZnO, Cr2O3 and CdO were used as active components. The samples were characterized by IR spectroscopy, X-ray phase analysis (Rietveld method), scanning electron microscopy (SEM-EDS), a Shimadzu AGS-X mechanical testing machine, and water- and benzene-vapour adsorption isotherms (BET) measured on a McBain–Bakr balance. The results showed that the catalysts possess both Brønsted and Lewis acid sites, exhibit type IV adsorption isotherms, and have specific surface areas of 180–198 m2/g and crushing strengths of 44–60 kg/cm2. Bentonite-supported catalysts were distinguished by relatively higher specific surface area, mechanical strength and resistance to poisoning. The study substantiates the feasibility of converting cheap local raw materials and technogenic waste into value-added catalysts (a resource-efficient, circular approach).
Copyright (c) 2025 Umrzokov Abdulla, Mukhitdinov Boxodir, Vapoyev Xusniddin (Author)
CLASSIFICATION OF NATURAL AND MAN-MADE EMERGENCIES
Improved or developed methodologies for analyzing various types of emergencies make it possible to predict them. However, these methods are generating debate on a number of issues, one of which is the problem of identifying the determining factors that shape the risk of natural and man-made emergencies in the study area. Addressing this and a number of other issues requires the use of specialized methods, which have been largely neglected to date. Many hazards are multifaceted (floods can be devastating for cities, paralyzing for flooded roads, or depleting agricultural lands). Based on the areas affected by the disaster, natural risks are classified by their magnitude.
Copyright (c) 2026 Khodjakulov Mukhtorjon Nazarkulovich (Author)
STRUCTURAL-DERIVATIONAL STUDY OF SYNONYMY, HOMONYMY, AND POLYSEMY PHENOMENA IN METALLURGICAL TERMINOLOGY
This article provides a profound structural-derivational analysis of synonymy, homonymy, and polysemy phenomena found in English metallurgical terminology. Due to the rapid development of the metallurgical industry's terminology under the conditions of modern scientific and technological progress, studying the semantic and structural characteristics of its lexical units is of significant importance. Throughout the research, the formation sources of metallurgical terms, their derivational models, as well as the semantic relationships between terms are systematically analyzed. In the article, the phenomenon of synonymy is highlighted through the expression of metallurgical terms in alternative forms, based on their scope of application and functional differences. The phenomenon of homonymy is examined through the example of terms that possess the same form but carry different meanings, and the mechanisms of their contextual differentiation are identified. Within the framework of the polysemy phenomenon, the expression of several interrelated meanings by a single term is analyzed based on the stages of their historical and functional development. Based on a structural-derivational approach, the study investigates metallurgical terms formed through word-building methods such as affixation, composition, and conversion, revealing the processes of their semantic expansion and specialization. Furthermore, the interactions of English metallurgical terminology with the terminology of other languages, particularly the Uzbek language, and translation challenges are partially covered. The results of this article serve as a theoretical and practical basis for systematizing metallurgical terminology, accurately interpreting scientific-technical texts, and compiling terminological dictionaries.
Copyright (c) 2026 O'tkirova Shahlo Asqar qizi (Author)
INTEGRATED GPU-BASED MODELING OF MEDICAL DATABASE MANAGEMENT SYSTEMS
The rapid growth of medical data volumes and the increasing complexity of analytical tasks require database management systems (DBMS) with high computational efficiency, scalability, and reliability. Modern information technologies, particularly graphics processing units (GPUs), provide powerful tools for accelerating data-intensive operations through massive parallelism. This paper presents an integrated overview of GPU architectures and their application in modeling and optimizing medical database management systems. We analyze key GPU architectural solutions (G80, GT200, and Fermi), the CUDA parallel programming model, and memory hierarchies, and demonstrate their relevance for medical data storage, processing, and signal analysis. The proposed integrated approach enables efficient processing of medical signals and images, supports large-scale databases, and reduces computational and economic costs in internet-based medical applications.
Copyright (c) 2026 Rakhimov Bakhtiyar Saidovich, Sobirova Sabokhat Kabulovna, Rakhimova Feroza Bakhtiyarovna , Allayarova Asal Akabarovna, Saidov Atabek Bakhtiyarovich (Author)
THE ROLE OF DIGITAL TWIN TECHNOLOGY IN ENHANCING INVENTORY VISIBILITY AND REDUCING BOTTLENECKS IN COMPLEX MANUFACTURING SYSTEMS
Industry 4.0 technologies as well as, Digital Twin technology has significantly changed the manufacturing industry as it allows real-time monitoring, simulating, and analyzing physical systems. The study examines how Digital Twin can be used to improve inventory visibility and reduce the number of bottlenecks in complex manufacturing environments. Digital Twin can be used to minimize inefficiencies and transform the overall work performance through the increased transparency of supply chains and streamlined production processes. Methods: The research methodology was quantitative with the secondary data sources at Bureau of Economic Analysis (BEA). The correlation analysis, paired t-tests, and multiple regression analysis were employed to evaluate the correlation between Digital Twin technology and the most important manufacturing parameters, including inventory management and production efficiency. Results: The findings show that Digital Twin technology can have a strong positive impact on the production efficiency and inventory visibility, especially with the help of real-time data and foretelling analytic tools. Nonetheless, the decrease in bottlenecks was not as significant as it should have been, and Digital Agility and Digital Flexibility had minimal impacts on reduction of the bottlenecks. The paper also indicates that Digital Twin technology will be beneficial in streamlining manufacturing, but the capability of workforce and system integration have to be tackled. Conclusion: Digital Twin can provide a viable option as a tool to improve inventory control and to minimize bottlenecks in manufacturing, to allow the creation of leaner, responsive, and greener manufacturing systems.
Copyright (c) 2024 Md. Rezaul Haque, Fazle Alahi Bhuiyan (Author)
Digital Transformation of the Construction Design Based on the Building Information Modelling
Background: The construction sector experiences an active digital evolution which Building Information Modelling (BIM) operates as essential technology to enhance design operations and project management and maintain better coordination between teams. Methods: The research used a quantitative approach to gather information through structured questionnaires which construction professionals including engineers and architects and project managers completed. The research team used purposive sampling to pick study participants who had direct experience working with BIM systems. The research instrument applied a 5-point Likert scale which evaluated BIM operational methods and fundamental BIM components including design efficiency and clash detection and visualization and collaboration and cost reduction and project success metrics. and Pearson correlation and multiple regression analysis to investigate the connections between different variables. Results: Projects that employ BIM will see significantly improved performance (i.e., example; clash detection (86.5%), visualization (84.1%), accuracy of the design (82.2%)). There is a strong positive correlation between BIM elements and the performance of the project as determined by correlation analysis (R=0.79). A regression also indicates that BIM can be accounted for as having contributed to the variations in project performance (R²=0.62). The role of design efficiency and clash detection are two important BIM elements that have been directly correlated to the success of construction based projects and their performance. Conclusion: Therefore, based on the findings of this study, it can be concluded that BIM serves a vital function in enhancing the construction process as well as improving project performance by increasing its efficiency.
Copyright (c) 2024 Innovative: International Multidisciplinary Journal of Applied Technology https://creativecommons.org/licenses/by/4.0
THE FACTORS AFFECTING ON THE GAS SENSING: REVIEW
In this review, we discussed the impact of oxygen vacancy, doping, film thickness, annealing temperature, and grain size on the gas sensing. One of the most common defects in thin films is oxygen vacancies, whose concentration varies based on the growth time and the microstructure of the synthesis films. The vacancies of oxygen considered centers for the accumulation of charge carriers, which reducing their losses resulting from recombination and contributes the increasing the life time of photogenerated charge. In addition, the oxygen vacant sites act as active adsorption centers, increasing the amount of chemisorbed oxygen species (O_2^-,O^-) which pull electrons from the conduction band and lead to the creation of a surface depletion layer. Silver atoms on the WO3 sensor surface enhance oxygen adsorbed, thus increasing the chemically adsorbed species such as O^(2-), therefore Ag doping of the WO3 layer successfully improves NO sensitivity. A thicker layer contains more pores and clusters than a thinner layer. In this case, even reactant gas is depleted oxygen and fresh oxygen are introduced, the length of the delay time required for the oxygen to penetrate the thick layer results in slow reabsorption of oxygen ions. Increasing the surface roughness contributes to providing a large surface area, which allows a greater number gas molecules to interact with the surface of film. The number of cracks in the thin film’s material is related to an increase in resistance, which depends on the layer thickness and applied deformation. Although the cracks may be pathway for gas entrapment, they are also very likely to cause an electrical breakdown that in this area. Annealing in air leads to increased oxygen vacancies generation which enhances gas sensitivity. The grain size has a significant effect on gas sensor based on n-type semiconductor like tin oxide, where electrons pass through potential energy barriers. The number of these barriers, which form at the grain boundaries, decreases as grain size increases.
Copyright (c) 2026 Azhar Mohammed Abd (Author)
MATHEMATICAL MODELING AND EFFICIENCY EVALUATION OF A HYDROSTATIC REGENERATIVE BRAKING SYSTEM IN QUARRY DUMP TRUCKS
This article examines the issues of improving energy efficiency in dump trucks operating under quarry conditions. The importance of hydrostatic regenerative technologies based on the recovery of kinetic energy lost during braking is scientifically substantiated. The study analyzes energy flows by considering vehicle operating modes, load levels, and driving conditions. The potential for reducing energy losses through the application of regenerative systems is identified. The processes of energy storage in hydraulic accumulators and its efficient utilization are evaluated. The results demonstrate the potential to reduce fuel consumption, improve environmental performance, and decrease exhaust emissions.
Copyright (c) 2026 Pulatov T. R., Umrzoqov J. A., Xamidov Sh. X. (Author)
ON THE PROBLEM OF WASTEWATER FORMATION, DISPOSAL, TREATMENT, AND DISCHARGE
The article examines the theoretical and applied aspects of wastewater generation, drainage, treatment, and discharge into water bodies under conditions of increasing anthropogenic pressure on aquatic ecosystems. It provides a systematic analysis of wastewater generation sources, their quantitative and qualitative characteristics, modern transportation and treatment technologies, and environmental requirements for discharging treated water into water bodies. The study substantiates the need to implement integrated water management solutions based on the principles of a circular economy and sustainable development. Particular attention is paid to the application of best available technologies, the digitalization of monitoring processes, and the minimization of environmental risks.
Copyright (c) 2026 Jumanazarova L. S. (Author)
SCIENTIFIC FOUNDATIONS OF THE HARMONISATION OF ERGONOMICS, PRODUCTION, AND HUMAN HEALTH
This article examines the relationship between ergonomics, production efficiency, and human health from both scientific and practical perspectives. The study rests on a straightforward premise: many workplace problems cannot be attributed solely to equipment failure or employee inattentiveness. In the majority of cases, the root cause lies elsewhere — in a workplace not adapted to the human being, a work pace that disregards physiological limits, an information flow that overwhelms the employee, and management that fails to identify hazards in time. The novelty of the study lies in treating ergonomics not as a narrow subject concerned with desk or chair specifications, but as an integral part of occupational safety, productivity, the prevention of occupational diseases, and safety culture. The analysis draws on the following documents of the Republic of Uzbekistan: Law No. URQ-410 "On Occupational Safety"; the Labour Code approved by Law No. URQ-798; Resolution No. CMR-819 on occupational safety regulations; Resolution No. CMR-263 on workplace attestation; and ILO Convention No. 155 ratified by Law No. URQ-969 . The analysis is further supported by international ergonomic standards, Resolution No. CMR-454 on occupational hygiene norms, and established findings from Russian and international ergonomics research.
Copyright (c) 2026 Azizbek Abdulazizovich Bakhodirov , Khabib Kholikovich Razzokov (Author)
SPATIALLY RESOLVED COMPOSITE RADIOLOGICAL AND HEAVY METAL RISK ASSESSMENT AROUND THE ARIARIA MUNICIPAL WASTE DUMPSITE: BUFFER ZONE HAZARD MAPPING AND POPULATION EXPOSURE ANALYSIS IN NIGERIA
Municipal waste dumpsites in low- and middle-income countries are often unlined and poorly regulated, releasing a complex mixture of heavy metals and naturally occurring radionuclides into surrounding environments. Conventional risk assessments typically evaluate these hazards independently, thereby underestimating cumulative exposure and associated health risks. There is an urgent need for spatially explicit, integrated risk mapping approaches to inform effective intervention strategies. A field-based assessment was conducted around the ariaria dumpsite, Nigeria, using three concentric buffer zones (0–100 m, 100–300 m, and 300–500 m). Data collection included (i) in situ background ionizing radiation (BIR) measurements (n = 120) using a calibrated dosimeter, (ii) soil sampling (n = 45) for heavy metal analysis (Pb, Cd, Cr, As, Ni) via ICP-MS, and (iii) groundwater sampling (n = 15). Radiological indices (AEDE, ELCR) and toxicological indices (HQ, HI, CR) were computed. Spatial distributions were generated using ordinary kriging, and a Composite Risk Index (CRI = normalized AEDE + normalized HI + normalized CR) was developed. Population exposure was estimated through GIS-based overlay with high-resolution census data. BIR decreased from 0.21 µSv/h (0-100 m) to 0.09 µSv/h (300-500 m), while Pb concentrations declined from 85 mg/kg to 22 mg/kg, indicating consistent spatial attenuation. The CRI exceeded unity up to ~250 m from the dumpsite. Within the 0–100 m zone, approximately 1,250 residents are exposed to CRI > 1, corresponding to ELCR > 10⁻⁴ and HI >1. A significant spatial correlation between radiological and toxicological hazards (R² = 0.68, p < 0.01) suggests common waste sources. It was concluded that integrated spatial risk assessment reveals that single-hazard approaches underestimate environmental exposure. Similarly, the buffer zone framework provides actionable guidance for resettlement and remediation, while the composite mapping approach offers a transferable tool for global dumpsite risk evaluation.
MATHEMATICAL MODELING OF THERMAL PROCESSES IN TRUNCATED CONICAL SOLAR WATER HEATERS
This article examines the mathematical modeling of thermal processes occurring in a truncated conical solar water heater collector. These collectors are crucial in enhancing energy efficiency and developing environmentally friendly heat sources. During the modeling process, convection, heat conduction, and radiative heat transfer processes are clearly expressed based on the Navier-Stokes equations. The complex nature of heat flow, the geometric characteristics of the collector, and the non-uniform absorption of solar radiation are all taken into account in the model. A three-dimensional system of differential equations, which describes the conservation of mass, momentum, and energy transfer, is used as the basis of the mathematical model. Also, the correct definition of boundary and initial conditions ensures that thermal processes are modeled in accordance with real conditions. The results of this study have served to increase the efficiency of solar water heater collectors and provide a deep analysis of heat exchange processes.
Copyright (c) 2026 N.R. Esanaliyeva (Author)
THE RELEVANCE OF DEVELOPING AN INNOVATIVE SYSTEM FOR REMOTE MONITORING AND MAPPING OF AGRICULTURAL LANDS
This study emphasizes that creating maps of agricultural lands through remote sensing and innovative methods is not merely a visual tool, but also a powerful instrument for complex data analysis, forecasting, and decision-making, and may serve as a foundation for sustainable development. The study substantiates proposals for solving land-use planning problems through the preparation of various maps based on satellite imagery. It also examines the main objectives of agriculture, including restoring an effective agricultural land management system, reviving land-use planning as a core management function, establishing an efficient monitoring system for assessing land conditions and qualitative changes in the land fund, financially supporting agricultural producers, ensuring the rational use of designated land parcels, and increasing the investment attractiveness of agriculture.
Copyright (c) 2026 Gʻulom Artikov, Anvar Mirzayev, Usmonjon Berdikulov (Author)
GIS-BASED APPROACHES TO THE CADASTRAL MANAGEMENT OF MUNICIPAL SOLID WASTE LANDFILLS: A FRAMEWORK FOR ENVIRONMENTAL MONITORING AND SPATIAL DECISION-MAKING IN UZBEKISTAN
Municipal solid waste landfills represent environmentally sensitive land-use objects whose management requires accurate registration, continuous monitoring, and spatially informed decision-making. In Uzbekistan, landfill governance remains constrained by fragmented cadastral records, incomplete environmental control, and weak integration between land administration and ecological monitoring systems. This study develops a GIS-based framework for the cadastral management of waste landfills by integrating cadastral, topographic, hydrological, soil, land-use, and monitoring data within a unified spatial platform. The methodology is based on geospatial database preparation, landfill boundary digitization, overlay analysis, buffer zoning, and sensitivity classification. The results show that the proposed framework improves the positional clarity of landfill registration, enables the identification of environmentally sensitive sites, supports the detection of land-use conflicts, and facilitates the prioritization of landfill monitoring. The study demonstrates that GIS can serve as an effective tool for linking cadastral management with environmental assessment and spatial governance. The proposed approach is particularly relevant for countries with incomplete digital cadastral integration and legacy landfill infrastructure.
Copyright (c) 2026 Artikov G‘ulom Abduraxmonovich, Nomozov Adham Almamat o‘g‘li (Author)
PROTECTIVE SHUTDOWN OF ADAPTATION IN CASE OF UNRELIABLE ESTIMATES IN THE WATER SUPPLY AND HEATING CONTROL SYSTEM
This paper examines the problem of improving the reliability of adaptive control in water supply and heating systems under conditions of noise, measurement asynchronousness, and residual estimation errors. A protection mechanism is proposed between the estimation unit and the fuzzy adaptation unit for the PID controller coefficients. After normalizing the current state and parameter estimates, a vector of invalidity indicators is generated. If the information is correct, the controller coefficients are determined using the Mamdani fuzzy inference mechanism. If the admissibility limit is violated, the adaptation is disabled, and control continues with fixed coefficients. This approach eliminates erroneous controller reconfiguration and maintains the continuity of the computational cycle.
Copyright (c) 2026 Khamdamov, Utkir Rakhmatillayevich, Hodjaeva Damira (Author)
CLASSIFICATION OF COMPLEX ANATOMICAL VARIANTS IN PEDIATRIC PATIENTS AFTER URANOPLASTY: AN INTEGRATED DIGITAL AND BIOCHEMICAL MONITORING APPROACH
Background: Cleft palate (CP) remains one of the most prevalent congenital craniofacial anomalies globally, affecting approximately 1 in 700 live births. Although uranoplasty restores anatomical continuity of the palate, post-surgical rehabilitation is frequently complicated by residual neuromuscular imbalances, altered occlusal dynamics, and compromised mucosal immune function. The absence of an integrated, multimodal monitoring framework limits the clinician's ability to detect and address these sequelae in a timely manner. Objective: This study aimed to develop and validate an integrated classification of complex anatomical variants observed in post-uranoplasty pediatric patients, and to evaluate the effectiveness of digital monitoring combined with biopolymer aligner-based orthodontic therapy on neuromuscular, occlusal, and biochemical outcomes. Methods: A prospective clinical observational study enrolled 150 children aged 6–12 years, divided into three groups of 50: a main group receiving digital monitoring with electromyography (EMG), T-Scan occlusal analysis, and biopolymer aligner therapy; a comparison group receiving conventional orthodontic treatment; and a healthy control group. Salivary biomarkers—alpha-amylase and secretory immunoglobulin A (sIgA)—were quantified at baseline and after 12 months. Statistical analysis employed the Mann–Whitney U test, Wilcoxon signed-rank test, and Spearman correlation (significance: p<0.05). Results: At baseline, masseter peak amplitude in the main group was 118.4 ± 12.3 μV, representing a 2.1-fold reduction versus controls (247.3 ± 18.6 μV; p<0.001). Muscular asymmetry index reached 31.4 ± 3.4%. Total occlusion time was prolonged approximately fourfold (1.82 ± 0.21 s vs. 0.46 ± 0.06 s in controls; p<0.001). Salivary alpha-amylase was elevated 2.2-fold relative to healthy peers. After 12 months, the main group demonstrated statistically superior improvements in all parameters compared to the comparison group (p<0.05 for all outcomes). Conclusion: Integrated digital monitoring combining EMG, T-Scan, and salivary biomarkers enables a precise, evidence-based classification of post-uranoplasty anatomical variants and substantially enhances rehabilitation outcomes. Early multimodal intervention is recommended for all pediatric patients following cleft palate repair.
Copyright (c) 2026 Innovative: International Multidisciplinary Journal of Applied Technology
CHINESE INVESTMENT IN UZBEKISTAN'S MINING SECTOR UNDER THE BELT AND ROAD INITIATIVE (BRI): STRATEGIC DRIVERS, NETWORK EMBEDDEDNESS, AND GLOBAL TRANSMISSION
Chinese mining investment in countries along the Belt and Road represents not only a deepening of bilateral economic and trade cooperation but also a new variable influencing the global economic landscape. Taking Uzbekistan as a case study, this paper constructs a three-stage analytical framework of "Strategic Drivers-Network Embeddedness-Global Transmission" to systematically examine the complete logic chain of Chinese mining investment, from its motivations and local practices to the transmission of global effects. The study finds that, at the strategic driver level, China's resource security needs and Uzbekistan's "resource-based development" strategy form a deep strategic coupling, providing the fundamental impetus for large-scale investment. At the network embeddedness level, Chinese investment deeply embeds itself into Uzbekistan's industrial system through technology transfer, infrastructure construction, and capital injection, reshaping its mining sector from a "point-based extraction" model into a "full-chain integration" model, generating significant technological spillovers and localization effects. Building on this, the paper focuses on demonstrating the global transmission effects of the investment: First, it reshapes global resource supply chains by constructing a Eurasian mineral resources corridor, enhancing supply diversity and resilience. Second, it innovates the "resource-finance-infrastructure" bundled model, offering an alternative development financing approach for Global South countries. Third, it promotes the rise of the Central Asian "land power" resource hub, subtly altering the global trade and capital flow patterns historically oriented towards maritime power. The study concludes that Chinese mining investment in Uzbekistan has become a crucial window for observing the "multipolarization" trend of globalization.
Copyright (c) 2026 Zhao Shengli (Author)
OPTIMIZATION OF LARGE-SPAN STEEL TRUSSES THROUGH MODIFICATION OF STRUCTURAL FORM
This study addresses the problem of improving the structural efficiency of large-span steel trusses, which are widely used in construction due to their simplicity and adaptability but are often associated with increased material consumption and complex stress states under non-nodal loading. A key issue arises when concentrated loads act between nodes, generating additional bending moments (M) and shear forces (Q) in the upper chord members, leading to unfavorable stress–strain conditions. To overcome this limitation, the research proposes a constructive approach based on the local reverse bending of the upper chord panels. The knowledge gap lies in the insufficient exploration of how modifying the geometric form of truss elements can influence internal force distribution and reduce material usage. The study investigates two variants of a 36 m span pentagonal steel truss: a conventional model with a straight upper chord and a modified model with pre-bent upper chord panels. Using numerical analysis in the LIRA-SAPR 2017 environment, both models were subjected to identical static and dynamic loading conditions. The results demonstrate that reverse bending significantly reduces bending moments and shear forces in the upper chord members, leading to a more efficient stress distribution. The optimal performance was achieved at a bending height of f=12 cm. The findings confirm that this method enhances load-bearing capacity, reduces structural deformation, and decreases steel consumption by up to 10–11% overall and 20–21% in upper chord elements. The proposed solution offers a practical and economically efficient approach for optimizing large-span steel truss design.
Copyright (c) 2026 S. Asliyev, M. Balgayeva (Author)