American Journal of Engineering , Mechanics and Architecture (2993-2637)
American Journal of Engineering, Mechanics and Architecture (2993-2637) is an international peer-reviewed journal published to reach excellence on Research and Scientific Development. The journal is not limited to a specific aspect of engineering and architecture but is instead devoted to a wide range of subfields in the engineering sciences, electrical, mechanical and architecture. Articles of interdisciplinary nature are particularly welcome. The journal strives to maintain high-quality of publications. There will be a commitment to expediting the time taken for the publication of the papers. The editorial board reserves the right to reject papers without sending them out for review. The journal also publishes innovative contributions on every aspect of the architectural endeavor.
Emergency and the Importance of Relationships in Mathematical Models of Elliptic Statistical Structures
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Copyright (c) 2026 American Journal of Engineering , Mechanics and Architecture (2993-2637)
Formation of the Mahalla System and Architectural-Planning Features in the Rural Settlements of Ancient Ustrushona (Case Study of Jizzakh Region)
This article examines the stages of formation of the rural mahalla system and its architectural and planning characteristics in the Jizzakh oasis, which historically constituted the western part of ancient Ustrushona. Based on archaeological evidence and historical sources, the structural organization of communal settlements that emerged around “koshk” (fortified estates) during the Early Middle Ages (5th–8th centuries) is analyzed. The study reveals the patterns of adaptation of settlements located along the Sangzor River and the Arnasoy lowlands to the natural landscape, as well as the spatial relationships between key elements such as the guzar (community center), alou-khona (communal gathering space), and religious structures. The findings contribute to a deeper understanding of the architectural evolution of the rural mahalla system, which developed under the influence of socio-economic conditions and defense factors.
Application of a Hybrid EKF-Bayesian Approach for Technical Condition Diagnostics of Gas Turbine Auxiliary Power Units
Ensuring the technical reliability and flight safety of gas turbine Auxiliary Power Units (APUs) is a critical task in aviation engineering. Traditional diagnostic methods, often reliant on visual inspections and fixed thresholds, are limited in detecting internal or early-stage faults. This study proposes a proactive hybrid diagnostic approach integrating the Extended Kalman Filter (EKF) and Bayesian Inference for real-time monitoring and fault forecasting of the APU. The EKF is employed to linearize nonlinear engine dynamics and filter stochastic sensor noise, while the Bayesian framework provides a recursive mechanism for fault probability estimation and classification. Experimental results based on 120 test cycles demonstrate that the EKF algorithm reduces the Root Mean Square Error (RMSE) of critical parameters (rotor speed, exhaust gas temperature, and oil pressure) by an average of 65–67% compared to traditional measurement methods. The subsequent Bayesian classification achieved an overall diagnostic accuracy of 95.83% and a sensitivity of 95.0%. Furthermore, Receiver Operating Characteristic (ROC) analysis yielded an Area Under the Curve (AUC) of 0.956, confirming the high discriminatory power of the proposed model. The findings indicate that the integrated EKF-Bayesian approach offers a mathematically rigorous and effective solution for the early detection and trend forecasting of malfunctions, significantly enhancing aviation safety standards.
Review the Behavior of eccentrically loaded RC Columns Strengthened using CFRP Bars and Sheet
This literature review highlights the use of Fiber-Reinforced Polymer (FRP) composites to strengthen reinforced concrete (RC) columns under various loading conditions. It focuses on two main methods: near-surface mounted (NSM) FRP reinforcement and external FRP confinement, often used in combination. Key findings indicate that NSM FRP enhances flexural capacity and seismic performance, particularly under eccentric and biaxial loads. In contrast, external FRP confinement improves axial load capacity but is less effective with increasing eccentricity. Hybrid systems, which integrate NSM FRP and external wraps, effectively mitigate debonding and buckling, enhancing strength and deformation capacity. The review also mentions analytical models that predict the behavior of FRP-strengthened columns. Applications of these methods include corroded, fire-damaged, or seismically challenged columns, confirming FRP composites as a valuable solution for reinforcing concrete structures.
Impact of Construction Waste on the Environment and Recycling Solutions
The rapid growth of urbanization and infrastructure development has significantly increased the amount of construction and demolition (C&D) waste generated worldwide. Improper disposal of construction waste has become a major environmental concern, leading to land degradation, air pollution, water contamination, and excessive consumption of natural resources. This study investigates the environmental impacts of construction waste and explores sustainable recycling solutions that can reduce environmental damage and promote sustainable construction practices. The research analyzes different types of construction waste materials such as concrete, bricks, wood, metals, plastics, and glass, along with their environmental effects. A literature review of previous studies on construction waste management and recycling techniques is presented. The study also evaluates recycling efficiency and waste composition using tabulated analysis. The findings indicate that recycling materials such as concrete aggregates, metals, and bricks can significantly reduce landfill waste and conserve natural resources. Implementing sustainable waste management strategies, improved recycling technologies, and government policies can enhance environmental sustainability in the construction industry.
Assessment of the Impacts of Atmospheric Temperature and Pressure on Solar Irradiance in Idah, Kogi State, Nigeria
This study assessed the impacts of atmospheric temperature and pressure on solar irradiance in Idah, Kogi State, Nigeria. That data of atmospheric temperature and pressure were collected hourly from 9:00 am to 6:00 pm on February 25, 2026, in a school called Mathson School, Idah, using a weather station, while solar irradiance was measured using a pyranometer software installed on a laptop, and connected to the internet. The results revealed that the solar irradiance varied throughout the day, with peak values occurring in the early afternoon, which corresponds to higher temperatures and lower atmospheric pressures. The correlation analysis showed that there was a weak positive relationship between temperature and solar irradiance (r = 0.065) and a very weak negative relationship between pressure and solar irradiance (r = –0.036). This correlation despite the weak relationship shows that the solar irradiance is directly proportional with the atmospheric temperature and inversely with the atmospheric pressure. These findings demonstrate that atmospheric conditions have influence on solar irradiance and this provide insight into local solar energy potential. In addition, the results provide an insight regarding the period of time in which higher solar energy is expected in this research area, Idah, Kogi state. It was concluded that though, the correlation coefficients between the solar irradiance with the atmospheric temperature and pressure are low, there exists a relationship between solar irradiance and the two atmospheric parameters considered in this work. It is recommended that solar energy systems in Idah be designed to utilize peak solar irradiance periods between 11:00 am and 3:00 pm. It is also recommended that data of many days or months be used for the similar work in future. Additionally, continuous monitoring of atmospheric parameters should be implemented for improved solar energy planning. This study is valuable as it will inform solar energy forecasting, optimize solar panel placement, and enhance energy output predictions, supporting effective deployment of solar energy systems in the region.
Review on Consolidate of Combinational Logic Circuit
This paper's learning objectives are to illustrate the chronical of a logic switching circuit. The study focuses on the evolution and use of logic throughout history in the field of computer and electronic applications. This essay focuses on design considerations, a few interesting facts, and a brief analysis of the fundamental requirements of logic fusion. Additionally, it improves students' comprehension of various Boolean function minimization techniques.
Robust Lane Detection Framework for Autonomous Vehicles Using Deep Learning and Computer Vision
The arrival of self-driving cars has made it even more important to have reliable and effective lane detection systems. Lane detection helps keep cars in their lanes while driving, making roads safer. This paper proposes a framework for real-time lane assistance comprising lane detection, tracking, marking recognition, and a warning when the vehicle is about to leave the lane. The framework uses OpenCV and convolutional neural networks (CNNs) to analyze video from a vehicle-mounted camera and estimate lane parameters such as position, slope, and curvature. These parameters let the framework determine the vehicle's position relative to the lane and steer it. Lane detection systems for self-driving cars must work in real time, adapt to varying weather and lighting conditions, and handle changes in road markings. The proposed framework effectively addresses these challenges and improves the safety and reliability of autonomous driving.
Experimental Investigation of Heating Element Performance with Bypass Tubes
This study presents an investigation of the thermo-hydraulic performance of a rotary air preheater heating element utilizing bypass tubes and wire coiled coil matrix turbulators. The work purpose is to improve heat transfer efficiency and minimize flow resistance while considering the practical problems observed in failed heating elements utilized in industrial units such as the Al-Hartha Thermal Power Station in southern Iraq. The experimental setup is intended for simulating working conditions of an air preheater under cyclic charging and discharging of hot and cold air flows. Air from a single matrix is switched between the two directions of flow using a valve-controlled system driven by an automated control panel. Three different types of bypass layout are tested in order to determine the best positioning and number of the tubes. Additionally, bypass tubes with various diameters (10, 15 and 20 mm) and shapes (circular and squared section) are tested. Also, three turbulators with different pitches are inserted into the bypass tubes to increase turbulence and enhance convective heat transfer. The results clarify the interlinked influences of bypass flow control and turbulent augmentation on the overall performance of stack heat recovery elements. The thermo-hydraulic performance for inline-tube arrangement rises on the order of 7.58% over the conventional element, while the 15 mm tubes deliver improvement of 15.47%. The cylindrical section outperformed the square section over examined Re range, with an improvement 23.49%, while the 5 mm pitch turbulator achieved an improvement of 23.92%.
IoT-Enabled Embedded System for Rash Driving Detection and Automatic Speed Control Using GPS and GSM
The loss of human life is the most significant loss that cannot be regained, in contrast to other property losses. Every year, a lot of people die in car accidents. Many different things have been tried to stop these road accidents. There are now better roads, and many road safety programs have been put in place. Many different technologies and methods have been developed to teach people to drive safely, but most haven't helped prevent accidents. The proposed system for this project monitors several vehicle parameters, including speed, engine speed, brake pedal status, and steering angle. An embedded microcontroller board measures all of these things. The goal is to learn about a driver's driving style by looking at how they use the gas and brake pedals. If the way a person drives meets the criteria for reckless driving, the system notifies the driver and, if the behavior continues, limits the vehicle's speed and sends a text message to the nearest police control room via a GSM module. The system also controls how fast cars can go in areas with a lot of people, such as cities and villages along the route. The GPS module system keeps track of the vehicle's location at all times. If it enters a city, the speed limit is set to a safe level.
Influence of Type of Solvent and Preparation of Oil-Containing Raw Material on Kinetic Dependences of its Extraction Process
The influence of a solvent on the extraction processes of cotton cake is established. The kinetic equations of the extraction processes are determined. The dependences of the extraction coefficients on the type of solvent and the type of oil containing raw materials used are revealed
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Laying and Protection of Water Pipelines in Conditions of Moving Sands
This article is devoted to the design and construction of settlements in sandy deserts, with an emphasis on creating a protected and comfortable living environment. Key aspects are considered, such as protection from natural factors (sand storms, heat and dust), water supply, as well as effective ways to protect water pipes and buildings from the effects of sand. Particular attention is paid to the need to create green protective strips and landscaping, as well as recommendations for laying utility networks and water pipes at depth, which minimizes the negative impact of sandstorms. The main architectural and planning solutions are provided, aimed at the sustainability of infrastructure and improving the microclimate in sandy deserts.
Noise-Absorbing Asphalt Technology in Uzbekistan and Its Ecological Efficiency in Cities
This article analyzes the introduction of noise-absorbing asphalt technology in Uzbekistan and its environmental efficiency in cities. The article examines the composition, principles of operation and practical impact of noise-absorbing asphalt pavements in the urban environment. The article shows that noise-absorbing asphalt not only significantly reduces traffic noise, but also helps to protect public health, improve the quality of the living environment and ensure environmental sustainability. At the same time, the article also highlights the application of innovative solutions to asphalt pavements, such as sensor technologies, temperature-adapting materials and waste recycling.
Current State of Water Supply and Surface Water Treatment in the Lower Amu Darya River Basin
This study evaluates the current condition of water supply and surface water treatment in the lower Amu Darya River, a major source of freshwater for Uzbekistan and Turkmenistan. The water resources of the lower Amu Darya face challenges due to reduced flow, climatic variability, irrigation demands, and limited treatment infrastructure. We analyzed hydrological data, water allocation policies, and existing water treatment practices to assess supply reliability and treatment efficiency. Results indicate persistent water scarcity, aging supply systems, and a lack of modern treatment facilities. Recommendations include enhancement of treatment infrastructure, integrated water resources management, and adoption of advanced purification technologies. These findings provide insights for policymakers and water resource managers aiming for sustainable water security in the region.
Low-Temperature, Low-Metal Consumptıon Thermosıphone Heatıng Devıce wıth Intermedıate Heat Carrıer for Solar Heatıng Systems
This study focuses on the development of a low-temperature, low-metal consumption self-regulating thermosiphon heating device with an intermediate heat carrier for solar heating systems aimed at improving energy efficiency and reducing material consumption. The research involves analysis of modern heating device designs, theoretical and experimental investigation of single- and two-phase heat exchange processes, and the development of mathematical models describing evaporation and condensation under natural thermosiphon circulation conditions. The proposed design consists of a hermetic housing divided into evaporation and condensation chambers equipped with steam confusors, ejectors, and a thermoregulating valve, which intensify heat transfer by increasing steam velocity and enhancing mixing in the condensation zone. Hydraulic separation from the main heating system reduces internal pressure and wall thickness, lowering metal consumption while maintaining structural reliability. The results show that the developed device improves heat transfer efficiency and enables 3–4% heat savings through self-regulation, making it suitable for application in solar heating systems and modern energy-saving technologies.
A Water Heater That Regulates Itself for Solar Heating Systems
A method for calculating the water intermediary in a multilayer stratified thermal storage tank used in solar heating and hot water supply systems has been developed. The intermediary has a constant cross-section and uniform perforation throughout its height. The examination of global and domestic practices for improving the performance of self-regulating active water heat accumulators in solar heating systems is ongoing. Innovative solutions for self-regulated stratified thermal storage systems are being developed. Conditions for achieving self-equilibrium in the self-regulatory components of hot water storage tanks are being identified, considering dynamic processes caused by unbalanced solar radiation. A theoretical investigation of water flow in perforated distributors with a constant cross-section under the influence of volume forces is being conducted. Additionally, a theoretical analysis of water collection in perforated collectors with constant cross-sections due to volume forces is taking place. A method for calculating water distribution and designing a self-regulating thermal storage system is currently being developed. An experimental exploration of the perforation in the water distribution system of a self-adjusting hot water storage tank is also underway.
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Enhancing the Thermal Performance of a Three-Pass Solar Air Heater Using Latent Heat Storage Materials: A Comprehensive Review
with latent heat storage materials (Phase Change Materials, PCMs) are reviewed to improve the thermal conductivity. The principle behind this integration is based on the high energy-storage density of PCMs, whose heat absorption and heat release occur at nearly constant temperatures, that enhances the system efficiency and smooths the convergence of the outlet air temperature. The enhancement of the air residence time and heat transfer rate is achieved by the three-pass flow pattern although more pressure drop and design complexity are introduced. A review of literature reveals that the use of PCMs brings about considerable improvement in the total thermal performance as compared to the conventional systems more so by way of prolonging the heating duration beyond the retardation of solar radiation. Proper PCM melting temperature and high thermal conductivity of PCM are important for efficient charging/discharging processes Major obstacles are the low thermal conductivity of typical PCMs which generally needs to be enhanced by means of ﬁns, metal matrices or by encapsulation methods. The core technical difficulties are the very low thermal conductivity of the ordinary PCMs, which usually needs to be enhanced by fin, metal matrices, or encapsulation methods. Leakage during melting and long-term material stability are also importantly design issues. Moreover, the hydrodinam¬ics of the three-pass configurations becomes increasingly intricate., thus rendering the airflow distribution and pressure drops as the dominant system optimization parameters. The literature on PCM incorporated three-pass heaters is still scarce, as the most of the works related to that of single- or double-pass collectors. There are important gaps in dynamic modeling of multi-pass systems with PCM, long-term cycling studies, and cost – benefit analyses. The review emphasizes the requirement of development of advanced numerical models, superior PCM composites with enhanced conductivity and system level integrated designs that can include reasonably complexity in thermo-technical performances. To sum up, the incorporation of latent heat storage materials into three-pass solar air heaters offers an attractive way to enhance the heat transfer performance, meanwhile, further work is required to solve the material, design and economic issues for large scale implementation.
Towards Sustainable Computing: Emerging Green Technologies and Energy Optimization in IT Systems
Green computing or sustainable computing is a radical style of information technology that seeks to minimize the effects of computing systems on the environment without necessarily affecting the performance and operation efficiency. Digital technologies, such as high-performance computing, data centers, and cloud infrastructures, have led to a significant level of energy consumption, emissions of greenhouse gases, and the accumulated electronic waste, which is becoming a major problem concerning the sustainability of the world. This paper also examines a broad spectrum of green computing technologies and solutions such as designing energy efficient hardware, virtualization, optimization of cloud resources, smart power management, and also disposing and recycling of electronic equipment in an environmentally friendly manner. It evaluates how well these strategies would lead to energy saving and cost reduction in their operations, and at the same time alleviate negative environment effects. Moreover, the studies examine the latest case studies and empirical knowledge to prove the practical utility of implementing green computing in industrial, academic and government IT systems. Economic and ecological implications of sustainable computing practices are also discussed in the paper and possible benefits in terms of carbon footprint, energy consumption, and resource wastage are presented. This study uses the cumulative knowledge of the existing literature and real-life applications to establish the best practices, major challenges, and trends of green computing adoption. The results indicate that incorporating green computing strategies will not only help in conserving the environment but also improving the performance of the system, its reliability as well as cost-effectiveness which creates an interesting argument as to why organizations need to highly consider the issue of sustainability in IT planning. This research should be used by the policy-makers, IT managers and researchers as a guideline to deploy and design environmental friendly computing solutions thus contributing to global energy efficiency and sustainable technological development.
Principles of Planning Landscape Design of a University Campus
This article provides a scientific analysis of the main principles of landscape design planning in a university campus. It addresses functional zoning, ecological sustainability, pedestrian circulation convenience, and aesthetic composition. In addition, the visual appearance of the campus landscape is examined, proposals for its improvement are developed, and the conclusions are presented.
Neural Style Transfer Using Deep Convolutional Networks: Principles and Applications
Neural Style Transfer (NST) has recently emerged as a revolutionary trend at the intersection of profound literacy and cultural expression. This new idea is based on how people naturally create things. It lets you mix material from one image with the style of another, creating a new kind of visually appealing image. This book talks about the ideas, methods, and workings of NST. NST is a new way to make art that combines photographs with rich content and the unique styles of famous painters, illustrators, and others. It does this by routing and manipulating point representations from pre-trained networks. The approach is based on optimising a total loss function that combines content and style losses. This lets images keep both the substance of the content source and the stylistic details of the reference image. This book goes into detail into the specialised parts of NST, showing how convolutional layers in deep neural networks capture the content and style of images. We talk about how to use loss functions and the iterative optimisation process to make beautiful compositions. We also look at how hyperparameters and loss weighting affect the transfer of information and style, which gives us more precise control over it. This work shows the wide range of operations that NST can do, in addition to the specialised ones. NST has made progress in several areas, including graphic design, fine arts, and computer vision. They have done everything from rethinking pictures as if they were painted by expressionist masters to making new textures and designs. This article gives useful examples and real-world use cases that show how NST could be used in the future. NST brings up new ways of talking about culture and gives both artists and technologists valuable tools. It can turn everyday photos into works of art.
Hybrid Composite Laminates using an AUXETIC Steel Core: A Numerical Investigation
The use of Fiber Metal Laminates (FMLs) provides a high-stiffness fibre-reinforced polymer (FRP) with ductile properties derived from metals; however, few studies have attempted to create hybrid FMLs that incorporate auxetic (negative Poisson's ratio) materials to enhance energy absorption characteristics. To investigate the mechanical behaviour of hybrid laminates composed of perforated steel metamaterials sandwiched between layers of Glass Fiber Reinforced Polymer (GFRP) and Carbon Fibers, a series of parametric studies using Finite Element Analysis (FEA) in SIMULIA Abaqus were conducted. This analysis focused on the development of a metallic core with a non-convex rotating unit geometry and a theoretical Poisson's ratio of -1. A Uniaxial Tensile Test was conducted to find the effective elastic properties of the Hybrid Material Structure. The results of this study showed that the Hybrid Laminate, a form of the Hybrid Structure, did not retain any auxetic characteristics found in its separate component, the Metal Core. This is contrary to the original theory used to develop these Hybrid Laminates, as the Hybrid Structure's Ultimate Poisson’s Ratio increased rather than decreasing as expected. The results further demonstrate that the high in-plane stiffness of the Composite Face Sheets, when bonded together with other sheet layers in the Hybrid Structures, limits the rotational mechanism necessary for producing the auxetic effect. This finding concludes that for the hybrid Fiber Metal Laminates to achieve the auxetic characteristics inherent in their Metal Core components, the interface design must be such that enough freedom is allowed for geometric variations. The Guidelines established in this study are intended to assist in the development of next-generation Metamaterial Composite Fabrics with sufficient geometric freedom.
Next-Generation AML Surveillance: Combining Real-World Evaluation and Precision Alerts for Improved Detection
The landscape of Anti-Money Laundering (AML) surveillance is rapidly evolving, driven by increasing sophistication in financial crimes and the need for more effective detection mechanisms. This article explores a next-generation AML surveillance framework that integrates real-world evaluation with precision alert systems to enhance the detection of illicit financial activities. Traditional AML approaches often rely on generic rule-based systems that generate a high volume of false positives, leading to inefficiencies and resource strain. In contrast, the proposed framework combines advanced data analytics, machine learning algorithms, and contextual evaluation of financial transactions to provide more accurate, actionable alerts. By employing precision alerts that are tailored to specific financial behaviors and risk factors, the framework aims to minimize false positives while ensuring that suspicious activities are flagged with greater accuracy. This article delves into the architecture of the system, outlining how real-world data evaluation and predictive modeling work together to improve detection and compliance. Through detailed case studies and practical applications, the paper demonstrates how this approach offers significant improvements in identifying complex money laundering schemes that may evade traditional methods. Furthermore, the integration of precision alerts offers a more proactive and targeted approach to AML compliance, enabling financial institutions to better allocate resources, streamline operations, and reduce overall risk exposure. The findings present a comprehensive roadmap for regulators and financial institutions seeking to implement next-generation AML solutions, ensuring more efficient, cost-effective, and reliable detection of financial crimes in the modern era.
Deep Learning–Based Facial Expression Recognition for Emotion Understanding in Human–Computer Interaction
Facial expression recognition (FER) has become an important field of study in computer vision and artificial intelligence because it could help machines understand how people feel. FER systems try to figure out how people are feeling by looking at changes in their eyes, mouth, eyebrows, and other parts of their face. They can tell if someone is happy, sad, angry, scared, surprised, or disgusted. Recent advancements in machine learning and deep neural networks have significantly improved the accuracy and robustness of emotion recognition models, enabling their deployment across diverse real-world applications. These applications encompass various fields, including mental health diagnostics, where FER can aid in the evaluation and treatment of psychological disorders such as depression and anxiety; education, where emotion-aware systems can promote adaptive and individualized learning environments; and human-computer interaction, where emotionally responsive interfaces improve user engagement and experience. Even though there has been a lot of development, there are still several problems that need to be solved. These include being able to reliably detect subtle and complex emotional indicators, being able to work well in different lighting conditions and when there are obstructions, and the ethical issues that come up when collecting and using facial data. To make sure that FER technologies are used safely and effectively in real-world systems, these problems need to be solved.
Influence of Diagnostic Systems on the Efficiency of Maintenance and Repair of Modern Automotive Engines
This article provides a comprehensive analysis of the influence of diagnostic systems used in modern automotive engines on the efficiency of service and repair processes. The rapid development of electronic control systems, digital sensors, and computerized diagnostic equipment in the automotive industry makes it possible to monitor the technical condition of the engine in real time. These systems allow for the early detection of engine malfunctions, the precise determination of their causes, and the optimal planning of maintenance and repair work. The introduction of diagnostic systems into service practice contributes to reducing repair time, efficient use of labor resources, reducing the consumption of spare parts, and improving the quality of service. Also, the reliability and service life of the car engine will increase, environmental indicators will improve, and fuel consumption will be optimized. The article scientifically and theoretically substantiates the practical significance of modern diagnostic technologies in service and repair processes, their economic efficiency and role in improving the maintenance system.
A Real-Time Deep Learning–Based Drowsiness Detection and Alert System for Enhanced Automotive Safety
The Comprehensive Drowsiness Detection and Alert Solution for Automotive Safety addresses the growing concern of road accidents caused by driver weariness, which is a factor in about 20% of incidents worldwide. Keeping drivers awake is very important for reducing dangers and saving lives. This research proposes a robust, real-time monitoring system that leverages computer vision and deep learning to detect early signs of fatigue and prevent accidents. The system uses a live camera feed to monitor the driver's face, paying close attention to how their eyes move and blink. A Convolutional Neural Network (CNN) analyses this data to detect long periods of eye closure, a sign of exhaustion. The system sounds an alarm as soon as it sees that the driver is sleepy. This non-intrusive method ensures continuous monitoring without causing discomfort or disruptions. The project is designed to be flexible and scalable so that it can be used as a standalone device in cars or as a mobile app. It makes sure that a wide variety of users can pay and access it by using inexpensive hardware and open-source software. The system can do more than just the basic tasks. It can also be integrated with additional functions, such as heart rate monitoring, vehicle speed control, and yawning recognition, making it much more useful and reliable. This approach can be used not only in personal cars, but also in commercial fleets, public transportation networks, and heavy industrial operations. The bigger effect on society is that it lowers the emotional and financial costs of car accidents, encourages safer driving, and generally makes traffic safer.
AI-Powered Early Fault Detection System in Electronic Circuits
Technical failures and problem may affect electric power systems and their essential industrial components, which in turn may affect the quality of electricity grid. Despite the significant developments in the plans of these systems, they may still face unexpected risks that may cause operational failures and decrease in efficiency. These failures may be from different sources which include thermal and systemic modifications during operation. It is essential to consider these malfunctions as the entire operating system may exacerbate the risks and create additional disruption and possibly add to the significant sudden losses. Thus, is is vital to enhance existing models in order to detect and classify failures and malfunctions and to place emphasis on these potential risks before they take place. This is very necessary to maintain the electrical systems to reduce and minimize the damage and support the total consistency of the system. This model will enable both earlier detection and accurate categorization to minimize the losses and deficiencies within the operating system and enhance the efficacy of automated and rapid procedure in the electronic circuits. The study may present a unified and structurally complete system that is capable oof analyzing the indicators obtained from the sound pumps and comparators, which attempt to align patterns to determine the disturbances and failures which affect power-related electrical mechanisms. It may utilize neural networks like the ANNs and the KNN algorithm, and employ the distinguishing LSTM model for process detection and error determination with unique efficacy and precision. The model is connected with automatic self-configured and automatic technologies to improve the operational capacity of the system and to improve its sustainability during and immediately after the identification of the fault, thereby enhancing the performance efficacy and consistency in the industrial motors fixed in the cells. The main motive of this study is the ability of the electronic system’s efficacy to identify the faults and predict failures that aim to anticipate malfunctions and provide immediate instant diagnosis before they take place. It also examines the system's ability to mitigate failures resulting from sudden and dangerous developments in critical systems. Therefore, it is necessary to improve and develop models capable of identifying patterns and classifying faults, and to attempt to link immediate service mechanisms with the system's capacity to reduce losses and improve the overall performance of the critical system, while ensuring continuous improvement and electrical circuit stability. This research addresses a gap in previous studies, which generally focused on fault detection in critical systems but failed to integrate immediate and self-remediation techniques within a comprehensive and balanced structural framework. It failed to implement a model on a real platform such as FPGA, in addition to the fact that it did not cover many tests in the event of branching and branching faults within the system, and real tests that involve pumps and comparisons of electronic circuits. Therefore, this study covers the research gap that helps in improving a balanced and consistent pattern that integrates artificial intelligence and automatic self-configuration mechanisms with real tests on FPGA, which helps in identifying and predicting faults and improving the accuracy and reliability of the system in a harmonious way.
The Concept for the Development of Higher Education Institutions in the Field of Architecture
This article examines contemporary challenges and development pathways for higher education institutions in the field of architecture, with a focus on aligning national educational systems with international standards and labor-market demands. The introduction outlines the rapid transformation of the architectural profession under the pressures of urbanization, climate change, digitalization, and growing social responsibility. Despite ongoing reforms, a significant knowledge gap persists in integrating practice-oriented learning, digital technologies, and sustainable development principles into architectural curricula, particularly in the context of developing countries such as Uzbekistan. The study employs a qualitative analytical method based on a review of national policy documents, international normative frameworks, and recent scientific literature on architectural education. Comparative analysis is used to identify mismatches between existing educational models and emerging professional requirements. The findings indicate that current architectural programs are often overly theoretical, weakly connected to industry, and insufficiently responsive to digital and interdisciplinary shifts. International experience highlights the effectiveness of competency-based curricula, transdisciplinary design studios, “living laboratories,” and hybrid learning formats in bridging this gap. The results demonstrate that adopting modular, project-oriented, and digitally supported educational models can significantly enhance graduate competitiveness and professional readiness. The article concludes that systematic integration of international standards, industry partnerships, and sustainable development principles is essential for reforming architectural education. The implications of this study are relevant for policymakers, university administrators, and educators seeking to modernize architectural education systems and prepare architects capable of addressing complex socio-environmental challenges of the 21st century.
The Effectiveness of Implementing a System of Risk-Adjusted Management Indicators in the Construction Sector
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Implementation of a Smart Neighborhood in the City of Urganch and Upgrading of Infrastructure Based on Eco-Technologies
This study covers the implementation of a smart neighborhood model in the city of Urganch and the renewal of urban infrastructure based on modern eco-technologies. The study substantiates the relevance of introducing digital control systems, energy-saving solutions, the concept of "green mobility", principles of sustainable urban planning and ecologically safe infrastructure elements. Within the framework of the proposed smart neighborhood model, smart solutions such as intelligent lighting systems, renewable energy sources, sensor-based monitoring, automated waste management system, bicycle and pedestrian lanes are integrated in accordance with the complex climate conditions. The results of the research show that development based on smart and eco-technological infrastructure increases the stability and efficiency of the city, reduces resource consumption and serves to create an environmentally safe, innovative urban environment in Urganch.
Designing Modern Market Complexes in an Environment of National Harmony
Today, the design of objects that meet modern requirements in the field of urban planning and architecture, while reflecting national heritage, is considered a pressing issue. Market complexes are an important component of the city economy, and they are not only a means of carrying out trade activities, but also an expression of cultural and spiritual unity, social ties and local identity. This article analyzes the methods of integrating national harmony, traditional architectural elements, materials and competitiveness criteria in the process of designing modern market complexes.