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.
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.
Copyright (c) 2026 American Journal of Engineering , Mechanics and Architecture (2993-2637)
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
ISO 31000:2018. Risk management — Guidelines. — Geneva: International Organization for Standardization, 2018. Committee of Sponsoring Organizations of the Treadway Commission (COSO). Enterprise Risk Management – Integrating with Strategy and Performance. — New York, 2017. Project Management Institute. A Guide to the Project Management Body of Knowledge (PMBOK® Guide). 7th ed. – Newtown Square, PA: PMI, 2021. Arifdjanova Z.D. Improving the organizational and economic mechanism for improving the effectiveness of management in construction enterprises. // Journal of Management Value & Ethics, 2024, Jan–March, pp. 152–159. Arifdjanova Z.D. Assessing the improvement of management efficiency in construction companies. // American Journal of Economics and Business Management, 2024, December, pp. 1337 – 1343. Arifdjanova Z.D. Improving the Management Mechanism for Increasing the Efficiency of Construction Enterprises. // Synergy: Cross – Disciplinary Journal of Digital Investigation, 2024, No. 2, pp. 59–63. Arifdjanova Z.D. Strategies for Improving Management Efficiency in Construction Enterprises. // Academic Journal of Digital Economy and Stability, 2025, Vol. 38, Issue 3, pp. 203 – 213.
Copyright (c) 2025 American Journal of Engineering , Mechanics and Architecture (2993-2637)
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.
Rehabilitation in the Study of Ischemic Stroke
At present, due to the rapid progress of treatment technology in the acute phase of ischaemic stroke, the mortality of patients has been greatly reduced but the number of disabled survivors is increasing, and most of them are elderly patients. Physicians and rehabilitation therapists pay attention to develop all kinds of therapist techniques including physical therapy techniques, robot-assisted technology and artificial intelligence technology, and study the molecular, cellular or synergistic mechanisms of rehabilitation therapies to promote the effect of rehabilitation therapy. Here, we discussed different animal and in vitro models of ischaemic stroke for rehabilitation studies; the compound concept and technology of neurological rehabilitation; all kinds of biological mechanisms of physical therapy; the significance, assessment and efficacy of neurological rehabilitation; the application of brain–computer interface, rehabilitation robotic and non-invasive brain stimulation technology in stroke rehabilitation.
Scientific Analysis of the Indicators of Strength, Elasticity, And Tension of Karakul Wool Fibers after Softening using Physico-Mechanical Methods
In Uzbekistan, the wool processing industry is not yet fully developed, and the semi-coarse fibers of local sheep are considered a difficult raw material due to their roughness, low elasticity, and disproportionate properties. This study analyzes changes in the strength, elasticity, and tensile characteristics of softened wool fibers. Based on regression modeling, technological trends and optimal parameters of seasonal fibers were determined. The results show that the softening of fibers increases production efficiency, and the developed models serve to prepare high-quality yarn and strengthen export potential.
This article describes the structure and operating principle of an automatic water dispenser based on an infrared sensor and a microcontroller. The device provides automatic water dispensing by detecting the user's movement without contact. The article analyzes in detail the functions of the main components of the automatic water dispenser system, including the IR sensor, microcontroller control board, electric pump, relay module and Li-ion battery. The automatic and manual control modes of the device, energy saving, hygienic convenience and application possibilities in everyday life are also considered. The results of this study are of practical importance in the design and improvement of automated water supply devices.
Fountains Their Main Types and Hydraulic Calculations
This paper investigates fountains and their main types with a focus on hydraulic design principles and calculation methods. Fountains play an important role in urban infrastructure and landscape architecture, providing aesthetic, microclimatic, and recreational benefits. However, stable and energy-efficient operation of fountain systems largely depends on the correct hydraulic calculation of flow rate, pressure head, jet velocity, and hydraulic losses. Improper design may lead to insufficient jet height, excessive energy consumption, or unstable operating conditions. In this study, fountains are classified according to their operating principles into free-flow, pressurized, and combined systems. For each type, the relationship between hydraulic parameters is analyzed using classical fluid mechanics equations. Mathematical models describing jet height, discharge velocity, and head losses in pipelines and nozzles are presented. The influence of pump characteristics and system losses on the achievable fountain height is evaluated through analytical calculations. The obtained results demonstrate that accurate hydraulic calculations allow optimization of pump selection and operating режимes, reduction of energy losses, and improvement of overall system efficiency. The proposed approach can be used in the design and modernization of fountain systems in urban and recreational areas, contributing to reliable operation and sustainable water use.
Abdurayimov Roʻzimuhammad Hasanboy Oʻgʻli
Hydraulic Couplers and Their Attachments
This article details the importance of hydraulic fasteners, their types, physical and chemical properties and additives that increase technological efficiency, which occupy an important place in the system of building materials. The process of solidification of hydraulic couplers in the aquatic environment, their mechanisms of strength formation and their application in modern construction have been analyzed from a scientific point of view. Also based on the effect of mineral and chemical additives on the quality of binders, environmental and economic efficiency.
Compatibility of Cotton Confectionary Fat with Natural Cocoa Butter
The article deals with the methods of hydrogenation and perietherification, the opportunity of obtaining cocoa oil substitute, which is close to the natural cocoa oil in its physical and chemical dualities as its freezing and melting temperature, solidity, the content of triglycerids of fraction and etc. New scientific, experimental and practical results of obtaining cocoa oil substitute have been presented.
The Role of Recycling in Building a Circular Economy
The growing global demand for resources and increasing waste generation pose serious threats to sustainable development (UNEP, 2023). Transitioning from a linear to a circular economy has become crucial. This article analyzes the environmental, social, and economic benefits of recycling, illustrated by practices in Sweden and the European Union. Findings indicate that recycling contributes to energy savings, waste reduction, job creation, and economic resilience. Nevertheless, recycling alone is insufficient without systemic approaches and supportive policies (Circularity Gap Report, 2024).
Sustainable Development of the Old Area of the City of Samara
The current study attempts to design for the development of Samarra's Old District. It is a mirror that reflects the effects of this civilization and the expression of the city's symbols through the integrated development of the examined region and its significance. Which will become a tourist attraction due to its cultural significance. It is also economically significant because it helps to the city's economic development and provides job possibilities for the unemployed. Which instills in the visitor a new perception of Samarra and, at the same time, instills pride in the city's youth when the heritage of their city is revealed to them. The archaeological significance of the project is one of the grounds for its selection. The reasons for choosing the project 1-The archaeological significance of the ancient district, which is a strong point for attracting tourists to the city and aids in the identification of the city's legacy. 2-To attract tourists, the city requires a space and an entertainment facility that welcome their activities and fits their needs. Project goals and objectives 1. Create communities near the Grand Mosque and give them their unique identity through a panorama that recounts the city's past to visitors and residents, as well as allowing them to see the heritage and glory of their forefathers. 2. Hold creative performances to communicate with other people's civilizations and cultures, as well as global scientific and technological growth. Visitors' definitions of Samarra's extended heritage, as well as the city's residents' definitions of what exists overseas and how it reflects current cultural development. Provide trade centers for various types of heritage goods, which is a lovely souvenir that visitors can preserve, and there can be. The research made a Sustainable development plan for the studied area and recommended some proposals for completion of the project.
Analysis of Fluid Flow through 90° Pipe Bends: Pressure Losses, Flow Separation, And Velocity Distribution
This paper gives a computational fluid dynamics (CFD) of the flow of an incompressible fluid through a 90deg pipe bend on the open-source SimScale platform. The flow of curved pipes is typified by the redistribution of velocity, development of a secondary flow and pressure losses so the primary goal is to determine the magnitude of the pressure losses and study the behaviour of velocity and the behaviour of separation as a function of Reynolds number and bend curvature. The parametric study of the elbow geometries is followed with variable curvature ratios (rc/D) and flow conditions (laminar and turbulent) on the geometries. Structured meshes in which the near-wall refinement has been used and steady Reynolds-averaged Navier-Stokes (RANS) turbulence models which are the standard k-e model and the SST k-o model are used to perform simulations with chosen transient cases to capture unsteady separation. The analysis has been conducted on pressure loss coefficients and velocity profiles, pressure contours, and the second flow patterns. The findings indicate the great effect of bend geometry and flow regime on flow organization and energy losses. The paper draws attention to the originality of utilizing an open-access CFD platform, which offers a reproducible numerical model, which can be used in teaching engineering and in initial design and subsequent experimental support.
The Problem of Modeling the Practice of Heat Treatment in the Preparation of Shafts of Technological Machines
In this article, the solution of the problem posed by the method of modeling the process of thermal processing is considered in solving the problems of managing and facilitating the technological process of manufacturing the shafts of technological machines and various techniques. As a result of theoretical studies, it was stated that the proposed thermal treatment model of shafts allows for rational control of the direction and amount of internal stresses in the preparation of shafts of technological machines and other techniques.
Mathematical Model for Improving Wear Resistance and Reducing Noise in Bevel Gear Transmissions
This paper presents a mathematical model aimed at evaluating the geometric accuracy of tooth surfaces and reducing wear and noise in bevel and hypoid gear transmissions used in automobile drive axles. The study considers the spatial kinematic and geometric characteristics of the grinding process based on the formate–tilt principle, in which the generating motions between the cutting tool and the workpiece are modeled using coordinate systems. Based on the parametric equations of the cutter head surface, the spatial theoretical equations of the gear tooth surface are derived, and the geometric deviations between mating tooth surfaces are evaluated using a discretization approach. The proposed model can be applied to analyze the meshing process, assess load distribution, and substantiate technological solutions aimed at reducing noise levels in bevel and hypoid gear transmissions.
Method and System for Constructing a Measuring Instrument Based on Digital Twin Technology
This article discusses an innovative approach to the design, manufacture, and operation of high-precision measuring instruments based on the concept of a digital twin. The proposed method enables the creation of a highly accurate virtual copy of a physical measuring device that integrates data on component geometric errors, assembly errors, static and dynamic system errors, and sensor characteristics. A multi-stage procedure for constructing such a digital twin is described, from design to calibration and operation. The architecture of the system, consisting of the physical subsystem of the device, its digital twin, and an integrated measurement management subsystem, is presented. A key advantage of this approach is the ability to predict measurement uncertainty, monitor instrument accuracy degradation in real time, optimize measurement trajectories on the virtual model, and, as a result, significantly improve the quality, reliability, and life cycle of measuring equipment. The method is illustrated using the example of constructing a coordinate measuring machine.
Deepfake Image Authentication with Deep Learning Technologies
As synthetic media has grown, deepfake images have become a big danger to the truthfulness of information and trust in digital media. These pictures were made by advanced generative models like GANs (Generative Adversarial Networks). They often include small visual differences that the human eye can't see. The goal of this project is to create a strong deep learning-based system that can find and sort deepfake photos with great accuracy. The model is trained on benchmark datasets like Face Forensics++ and Celeb-DF using Convolutional Neural Networks (CNNs) and transfer learning techniques. The suggested system focusses on learning features that can tell the difference between actual and fake photographs. It does this by looking for patterns like pixel-level aberrations, irregular illumination, and face asymmetry. The experimental results suggest that the model can accurately identify deepfake content, which is important for digital forensics, social media moderation, and information security.
Analysis of Foreign Impurities Contained in Fiber
This article presents experiments conducted in production conditions, changes in the structural composition of cotton and its characteristic parameters during technological processes.
changes in the technological process of cotton structure parameters
Design and Structure of Functional Textiles for Bed Applications
The analysis of medical fabrics showed that the assortment continues to develop, and new fabrics with improved consumer properties appear.
Impact of Advanced Composite Tubes on the Efficiency and Durability of Shell-and-Tube Heat Exchangers in Corrosive Petroleum Environments
This paper investigates the influence of a NCET on thermal performance and durability of S&T HE operating in corrosive media like that found in petroleum production. Traditional carbon-steel tubes corrode and erode, as well as foul up the process so that heat is not effectively transferred resulting in less efficiency, more frequently down time and costly servicing. This covers recent research on fibre-reinforced polymer and metal–matrix composite tubes for corrosion resistance, thermal conductivity, tensile strength and long-term stability when subjected to high temperature with pressure in a multiphase flow environment. A theoretical comparison of total heat-transfer coefficients, pressure drop and anticipated service life between composite and metallic tubes is generated. Consideration is given to design issues such as tube–sheet attachment, compatibility with current shell-and-tube layouts, and life-cycle cost effects. The outcomes should demonstrate the capability of suitably designed composite tubes to greatly improve performance and service life, while controlling corrosion failure. Guidelines for metallic and composite selection for petroleum heat exchangers are also presented, along with research needs for future experimental and industrial-scale work.
Powder-Based Additive Manufacturing: A Comprehensive Study of Materials, Process Parameters, Equipment, And Economic Efficiency
The rapid development of powder-based additive manufacturing (AM) has created new opportunities for producing complex metal components with controlled microstructure and high functional performance. Despite the widespread adoption of AM systems, the combined influence of powder characteristics, process parameters, and machine architecture on the final quality of printed parts remains insufficiently clarified. This work presents an integrated experimental and analytical investigation covering material properties, energy–material interaction, equipment capabilities, and the economic feasibility of industrial AM deployment. The results demonstrate that optimized powder preparation combined with energy-efficient parameter windows can significantly reduce microstructural defects and improve mechanical consistency. The findings provide new insights into the integrated optimization of materials, process parameters, and equipment selection, offering a practical decision-making framework for industrial implementation of powder-based AM.
Modern Strengthening Approaches for Aluminum Alloys: From Precipitation to Ultrafine-Grained Structures
The rapid evolution of transportation, energy, and aerospace technologies continues to increase the demand for aluminum alloys with superior combinations of strength, ductility, and thermal stability. Meeting these requirements relies on a deep understanding of the microstructural mechanisms governing deformation and strengthening. Over the last decade, substantial advancements have been achieved in the development of multiscale strengthening strategies, where atomic-level solute interactions, nanoscale precipitates, and submicron grain structures are engineered synergistically to optimize mechanical performance. This review consolidates recent experimental and theoretical progress in precipitation engineering, solute–dislocation interactions, and grain refinement through SPD. A comparative assessment of strengthening efficiency, stability under service temperatures, and applicability to industrial-scale processing is provided. The article also outlines remaining challenges and identifies promising routes toward designing next-generation aluminum alloys optimized for lightweight, high-performance structural applications.
Development of the Integrated Flood Hazard Index (FHI) for a Multi-Criteria Assessment of Mudflow Hazard
The article presents a comprehensive approach to the quantitative assessment and mapping of debris-flow hazard at the regional scale (using Samarkand Region as a case study) through the development of an integrated Flood Hazard Index (FHI). The index is constructed using a Multi-Criteria Analysis (MCA) framework and incorporates six key thematic layers: precipitation intensity (CHIRPS), flow accumulation (HydroSHEDS ACC), terrain slope (SRTM), distance to surface water bodies (JRC Global Surface Water), vegetation index (MODIS NDVI), and global land-cover data (ESA WorldCover). Data processing was carried out within the Google Earth Engine (GEE) environment, while layer integration was performed using normalization procedures and the Weighted Linear Combination (WLC) technique. The resulting FHI map delineates four hazard classes (very low to high) and reveals the spatial concentration of high hazard levels in the mountainous and piedmont catchments of the Middle Zarafshan. The methodological principles and datasets employed in the study are aligned with contemporary practices in satellite remote sensing and GIS-based hazard assessment.
Research and Testing of Basalt Fiber Reinforced Concrete Beams on Slope Section
In this article, the strength of reinforced concrete beams reinforced with basalt fibers in the slope section was studied experimentally and theoretically. The role of fibers in the concrete structure, their effect on crack elimination and their contribution to shear strength were analyzed. According to the results of laboratory tests, it was found that basalt fibers increase the shear strength and energy absorption capacity of concrete in the slope section. The results of the studies were compared with ordinary reinforced concrete, and suggestions were made on the optimal fiber content.
Geotechnical coal mining integrates geological, geomechanical, and engineering principles to ensure the safe and efficient extraction of coal resources. As mining operations progress to deeper and more structurally complex deposits, understanding the mechanical behavior of rock masses, stress redistribution, and ground stability becomes increasingly critical. This study examines key geotechnical factors influencing coal mine design, including rock mass characterization, slope and roof stability, subsidence prediction, groundwater control, and the application of monitoring systems for early hazard detection. Modern methods such as numerical modeling, geophysical exploration, and real-time geotechnical monitoring are highlighted as essential tools for improving mine planning and preventing failures such as roof collapses, gas outbursts, and landslides. The research emphasizes the importance of integrating geotechnical risk assessment into mining operations to enhance worker safety, optimize resource extraction, and reduce environmental impacts. Findings indicate that geotechnically informed decision-making significantly improves mine stability and sustainability, especially in regions with complex geological conditions.
Review on Sustainable Concrete: Alternatives to Cement, Gravel, and Sand
Concrete is the most widely construction material in the world due its easy formation and availability of raw materials. The disadvantage of its use was cement since it responsible of most CO2 emissions in world. Besides that, due to rapid publication growth, the waste materials generated by humans, such as plastic, glass, and non-biodegradable materials, harm the environment, so most research has involved incorporating waste materials in concrete to create an eco-friendly concrete. In this research, some studies that replaced cement with silica fume, palm ash, and fly ash, sand with glass powder and PET, gravel with crushed concrete and rubber were reviewed.
Development of Machine Learning Platforms that Accelerate Drug Discovery and Molecular Screening for Cancers, Autoimmune Diseases, And Neurological Disorders
The emergence of machine learning (ML) systems has gone a long way in advancing drug discovery, especially in the face of complex diseases including cancers, autoimmune diseases and neurological diseases. The combination of ML algorithms and genomic, proteomic, and clinical data has a tremendous potential to be used in predicting the therapeutic targets, in accelerating the drug screening process, and in improving the molecular interactions. This paper will discuss some of the ML methods, such as deep learning, reinforcement learning, and generative models, in drug discovery and molecular screening of these diseases. Moreover, the article raises the problems related to the implementation of ML to large-scale molecular data, the ethical issues of the implementation, and the necessity of the explainability of the ML models. Cases of MLs used in oncology, autoimmune disorders, and neurodegenerative diseases are described to demonstrate how the technologies have been used to aid in the early diagnosis of diseases, repurposing of drugs, and the creation of precision medicine. The combination of quantum computing, blockchain, and AI-based platforms are also discussed and their transformative power that should be used to ensure healthcare data security and enhance the efficiency of drug discovery pipelines. The article ends by stating that interdisciplinary work and data-sharing models are vital to the achievement of the full potential of ML in healthcare innovation.