Metallurgical and Materials Engineering (E-Journal)
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Problems of using BIM in Variant Design of Reconstruction Processes in Underground Parts of Buildings and Structures Using Universal Machines
Get PDFBuilding information modeling (BIM) is quickly transforming the construction sector, with significant improvements in project results. In recent years, as the construction industry has shifted from new building construction to building maintenance and usage, the need for BIM has increased. The life cycle of a building can be divided into several periods, the largest of which are the stages of design, construction, operation, and demolition of the building. The process of building information modeling mainly affects the building design and construction stages, minimally affecting the stages of operation and demolition. This is influenced by a number of factors, such as the low level of development of regulatory literature, or the lack of a modern technical base for the implementation of measures for the operation of the building using information models. As the development and use of BIM in new construction projects becomes more common, the construction industry begins to worry about and discuss the implementation of digital and intelligent management by creating As-is BIM for existing buildings and using BIM in the operation, maintenance, and building renovation or demolition phases. Processes of reconstructing underground parts of buildings and structures cause special challenges. This article summarizes the existing practices and concerns in this field, outlining vectors for further research and efforts
HIV Infection And Neonatal Outcomes In Pregnant Women Living With Hiv In Iran: A Systematic Review
Get PDFBackgroundPregnant women worldwide face a significant public health problem caused by HIV infection. In addition to the risk of mother-to-child transmission, it can result in significant complications and detrimental pregnancy and neonatal outcomes. No comprehensive evidence is available to measure the neonatal outcomes of HIV infection in pregnant women in Iran. This study aimed to assess neonatal outcomes of HIV infection in pregnant women in Iran.MethodsThe search for international databases, including PubMed, Scopus, ISI, and Embase, as well as all national databases, was done systematically until September 25th, 2024. The inclusion criteria encompassed any records reporting neonatal outcomes among pregnant women in Iran. The study outcomes included any neonatal implications related to HIV infection in pregnant women. ResultsA total of seven studies with participating 497 pregnant women living with HIV were identified. Abortion was the most common adverse pregnancy outcome. The proportion of newborns with HIV infection varied from 0% to 25.7%. The live birth rate exceeded 95% in most studies. Prophylaxis has been initiated for all newborns. Infant growth was within the normal range for the majority of infants.ConclusionAdverse neonatal outcomes among pregnant mothers with AIDS in Iran are quite low, and most of them receive care
Ai-Driven Adaptive It Training: A Personalized Learning Framework For Enhanced Knowledge Retention And Engagement
Get PDFIn traditional training designs, insufficient attention is paid to build an efficient knowledge management process because of usual generic training approaches, which leads to the lack of performer interest and engagement, repetitive learning, and minimal knowledge retention. This paper discusses about an intelligent IT training model which has been developed to automate the process of selecting appropriate material, increasing learner interest, and improving the effectiveness of training. Here it is important to note that the system uses AI, ML, NLP, and Cloud Computing to make changes to the content depending on the learning outcomes, statistics, and comments from the learners. The main components of the proposed system are the data acquisition sub-module, the AI core engine, and the learning improvement sub-module to achieve real-time training. The effectiveness of the system was, therefore, tested under controlled experiments with 200 IT professionals in which the product of adaptive learning based on artificial intelligence was compared with traditional models of training that employ static approaches. The outcome as per the tests showed that Interactive training through the AI system improved knowledge retention by 35% and increased the level of engagement by 40% and reduced the training time among the user by 22%. Moreover, the model aided by artificial intelligence was completed at a 94% level and it is higher compared to traditional methods
AI-Driven Emergency Response System For Vehicles: Enhancing Safety And Assistance
Get PDFThis research introduces an innovative AI-driven emergency response system for vehicles designed to detect, analyse, and respond to emergency situations in real-time. By integrating multiple sensors, machine learning algorithms, and communication technologies, the proposed system minimizes response time and enhances the effectiveness of emergency interventions. The system employs a novel hybrid deep learning architecture that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to process multimodal data streams from vehicle sensors, wearable devices, and environmental monitoring systems. Experimental results demonstrate a 37% reduction in emergency detection time and a 42% improvement in the accuracy of severity assessment compared to conventional systems. The implementation achieves a real-time processing capability with a latency of less than 200 milliseconds on standard automotive hardware platforms. This research contributes to advancing vehicle safety systems and provides a scalable framework for future intelligent transportation infrastructure
“Online Cosmetic Shopping Trends Among Women: A Demographic And Empirical Analysis In Gujarat”
Get PDFThe impact of the proliferation of e-commerce on the purchasing behaviour of female consumers regarding cosmetics in Gujarat, India. The quantitative study is demonstrating different demographical factors which impact on utilization of internet for cosmetics shopping among women. Data on the perspectives was collected from 500 female respondents from various age categories, economic classes, and employment statuses through a structured questionnaire and statistical analysis. This study explores how much brand awareness, brand loyalty, and brand association influence online buying behavior and purchase decisions. Data shows that demographic factors including age, income, and education significantly influence consumer choices and online purchasing behaviors. Insights of findings enhance the understanding of consumers' decision-making process in the context of the digital marketplace and guide strategies for e-commerce platforms and businesses in the cosmetics industry
Effect Of Carbon Fiber Reinforcement On Square Aluminum Cross Section For Automotive Applications
Get PDFThe studies on thin- walled structures have concentrated on structural optimization substantially for enhancing crashworthiness and light weighting, whilst fairly little attention has been paid to analysis of cost effectiveness of an optimized structure. How to develop cost-effective products has always been a primary thing pursued by enterprises in different ways. To address this issue, this study aims to interpret a methodical approach for exploring the goods of colorful material grades and structural dimension (e.g. wall consistence) on cost effectiveness relative to crashworthiness performance. Crashworthiness of a material is a measure of its capability to absorb energy during a crash. A well- designed crash box is necessary in guarding the expensive vehicle factors. A square, cold-blooded ray of aluminum/ CFRP was subordinated to dynamic axial cargo. Mixes are effective, to deal with tensile loads, than essence. Nowadays, essences are replaced with mixes owing to their advanced strength to weight rate and are considerably used in automotive operations. Modeling and analysis of compound crash box was done on CATIA V5R21 & ANSYS workbench. Manufacturing of mongrel crash box will be done using open molding system. Testing of mongrel crash box performed on UTM for bending test.  
Effect Of Predictive Nursing Intervention On Preventing Deep Venous Thrombosis Of The Lower Extremity After Hip Arthroplasty
Get PDFObjective: To explore the preventive effect of predictive nursing on deep vein thrombosis (DVT) in lower limbs after total hip replacement.
Methods: A total of 64 patients who underwent total hip replacement in our hospital from May 2022 to May 2023 were selected for this study. Patients were randomly divided into observation groups and control groups according to different nursing interventions. The control group received routine nursing intervention, and the observation group was given predictive nursing intervention based on routine nursing. The blood flow velocity, harris score, DVT of lower limbs, length of hospital stay, and adverse reaction were observed in the two groups.
Results: Before nursing intervention, there were no significant differences in blood flow velocity and harris score between the 2 groups (P > 0.05). After predictive nursing intervention, the blood flow velocity and harris score in the observation group were better than those in the control group (P < 0.05). There was no significant difference in the incidence rate of aches, swell, and infection in lower limbs between the control group and the observation group (P>0.05), whereas the incidence rate of DVT in the observation group was significantly lower than that in the control group (P < 0.05). In addition, the average length of hospital stay and incidence of total adverse reactions in the observation group was lower than that in the control group, with a significant statistical difference (P < 0.05).
Conclusion: Predictive nursing intervention has an ideal effect on the prevention of DVT in lower limbs after total hip replacement, and this clinical popularization has a broad prospect
Mathematical Modelling of Risk Management in the Shipping Industry
Get PDFSupply chain risk management (SCRM) is primarily a process of systematic identifying, assessing, and mitigating risks within supply chain systems. Despite its complexity and criticality, the offshore and marine industry, particularly the rig-building segment has received limited attention in SCRM literature. This study centers on managing risks in oil rig building projects. A structured risk mitigation framework is proposed to comprehensively identify potential risks, filter out minor ones, and prioritize the remaining based on their impact. A mathematical model is then developed to analyze one of the most significant risks: raw material price fluctuation. To quantify this risk, Monte Carlo simulation is applied using the Risk Solver platform. The study presents two case scenarios demonstrating the implementation of various risk management strategies and evaluates their effectiveness in enhancing the resilience of the rig-building supply chain
Real-Time Monitoring And Assessment System In Continuous Monitoring Of System Workloads And Performance Using Soc Architectures
Get PDFIn modern SoC designs, balancing energy efficiency and performance is crucial. This research proposes a novel approach to dynamically adapt communication protocols (AXI, AHB, APB) based on real-time system requirements and workloads. The goal is to develop an adaptive mechanism that intelligently switches between these protocols or adjusts their configurations to optimize power consumption and processing efficiency. The proposed research focuses on "Dynamic Protocol Adaptation in SoC Architectures for Energy Efficiency and Performance Optimization," aiming to transform the management of communication protocols within SoC designs. The core of this research involves developing a Verilog-based system capable of dynamically switching between AXI, AHB, and APB protocols based on real-time system demands. By incorporating a real-time monitoring system to assess current workloads and performance metrics, this approach seeks to optimize both energy consumption and processing efficiency. The novelty of this research is twofold: firstly, it introduces a dynamic adaptation mechanism that contrasts with traditional static protocol implementations, enabling more flexible and context-aware operation. This adaptability ensures the most appropriate protocol is used according to the system's specific requirements at any given time. Secondly, it simultaneously addresses energy and performance optimization, which is a pioneering dual-focus approach. The expected outcomes include enhanced system efficiency, with significant reductions in power consumption and improvements in processing performance. By tailoring protocol use to actual operational needs, the research aims to improve the overall effectiveness and robustness of SoC designs. Validation will be achieved through comprehensive simulation and real-world testing of the proposed system. This includes comparing the dynamic adaptation approach against static protocol implementations in terms of energy efficiency, performance, and design complexity. The results will be analyzed to demonstrate the practical benefits and viability of the dynamic adaptation mechanism, ensuring that the proposed system is both theoretically advanced and practically applicable, offering scalable solutions for integration into existing SoC architectures
FIR Management System In Dapps Using NFT
Get PDFThis article suggests a decentralized First Information Report (FIR) management system based on Blockchain technology and Non-Fungible Tokens (NFTs) to solve the inherent problems of data tampering, manipulation, and untransparency in conventional police complaint systems. The suggested system uses Ethereum-based smart contracts to automate the entire process of FIR management, from submission to disposal, ensuring that every step is logged on an immutable ledger. Every FIR is tokenized in the form of a distinct NFT, an auditable digital certificate that can be traced and made transparent across its life cycle. Third web integration also makes it easy to deploy and manage NFTs, as there is an easy-to-use interface for stakeholders. Moreover, the system preserves the confidentiality of sensitive data by encrypting it, with the blockchain serving as a secure, transparent layer that provides accountability without sacrificing data confidentiality. This decentralized method provides real-time monitoring of FIRs and addresses the inefficiencies and vulnerabilities of centralized systems. Finally, the suggested solution increases public confidence in law enforcement by providing the integrity and transparency of the complaint management process