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In the construction of any structure, the most important factor considered today are cost of construction and ability of the building to resist loads and earthquakes. Research is going on about various precast composite technologies to get a structurally strong system yet with reduced time and cost of construction, thus making it an affordable structural system for modular construction. Considering these factors, light gauge steel or commonly known as cold formed steel and precast ferrocement composite structures are gaining popularity in the Indian construction industry. This article is an attempt to review structural behaviour of innovative use of LGS and Ferrocement, sandwich panel composite construction. In the present research work, Finite Element analysis is done for typical residential building made of precast ferrocement panels combined with light gauge steel composite structure. Finally, stresses in the ferrocement element are checked with experimental values thus determining the load carrying capacity of the structure subjected to dead, live and seismic loads. Overall proving this load bearing composite construction system to be more effective with respect to speed of construction, cost of construction and affordability at the same time enhanced structural performance. Thus, a practically enhanced solution to substitute the conventional RCC structure is possible using this LGS Ferrocast/ferrocement composite construction technology. The assumption for this composite technology is that all ferrocement structural components are factory made in custom sizes under strict quality control as to achieve desired permissible stresses.

The aim of the present research is on the automobile application of magnesium matrix composites. To this purpose, optimal mechanical properties of MMCs are studied through the conduction of an experimental investigation. In this research, eight samples are to be considered based on the use of various reinforcement material types and their percentage. Magnesium matrix composite samples are to be manufactured by the use of the stir casting process. The following mechanical properties are to be calculated for every sample: tensile strength, flexural strength, impact resistance and hardness. The experimental results show that the 6 th sample, which is a magnesium matrix reinforced with graphite material at the rate of 10%., was among those with the highest mechanical properties in terms of tensile strength , which was 135 MPa, flexural strength, which amounted to 120 MPa, impact resistance, which reached 7.0 J, and hardness, which was 97 HV. Therefore, one can make a conclusion that it is important to optimize the reinforcement material and its percentage when considering the possibility to improve the mechanical performance of MMCs. That said, the given research offers insights into the potential of MMCs as lightweight materials with high performance in vehicle construction.

The adoption of green hydrogen in India’s transportation sector represents a promising solution to the country’s energy challenges. However, various barriers hinder its large-scale implementation. This paper employs a fuzzy Interpretive Structural Modeling (ISM) approach to identify and analyze the barriers affecting green hydrogen adoption. The Structural Self-Interaction Matrix (SSIM) and Initial Fuzzy Reachability Matrix (IFRM) were used to assess direct relationships between barriers, while level partitioning and the final fuzzy reachability matrix provided a hierarchical structure. The fuzzy digraph visually mapped the relationships, and a cluster of barriers diagram identified clusters based on driving power and dependence. Key barriers, such as “Technological Immaturity,” “Inadequate Regulatory Frameworks,” and “Policy Inconsistencies,” were identified as foundational challenges. Resolving these barriers will yield substantial positive effects across the network, streamlining progress in adopting green hydrogen in India’s transportation sector. The analysis offers a strategic pathway for policymakers and stakeholders to prioritize interventions for this clean energy technology.

This project looks at the best locations for Distributed Generation (DG) units in power distribution networks to reduce system losses and simultaneously enhance voltage profiles. The suggested methodology makes use of a hybrid optimization approach that blends fuzzy logic with the Particle Swarm Optimization (PSO) and Golden Section Search Algorithm (GSS). To evaluate the effectiveness and robustness of the suggested method, the study focuses on the IEEE-15 bus and IEEE-69 bus systems as test cases. This project thoroughly evaluates the suggested methodology on the IEEE-15 bus and IEEE-69 bus systems in order to validate and assess it. Comparative research indicates that fuzzy logic hybrid PSO and GSS are better than classical optimization techniques. The results demonstrate a noticeable improvement in loss reduction and voltage profile improvement

In this research work, the vacuum annealed stainless steel samples were subjected to a constant load. The wear behavior of AISI 431 sample were examined by using pin on disc wear tester. The vacuum annealing were used to preserve the stability between ductility and brittleness. The samples were created in cylindrical shape with a length of 40 mm and diameter 8mm. For this current research, 3 samples are treated at 600°C, 660°C, 820°C temperatures and they were assigned asA1, A2 and A3 respectively. The outcome of vacuum annealing is that to reduce the hardness and increase in ductility, to overcome the material from defects and release internal stress. The hardness, wear behavior were measured for the treated and untreated samples. To evaluate the wear behavior, comparison of results, wear test studies and scanning electronic microscope analysis were done.

This study optimizes the production of activated carbon (AC) from two distinct agricultural wastes, barley husk and maize cob. The process is refined using the Taguchi method with the goal of enhancing water treatment techniques. The study emphasizes how crucial it is to make the transition towards renewable and affordable raw materials for the manufacturing of AC given the predicted expansion of the worldwide demand for AC. The study assessed the impact of four crucial variables on the production and quality of AC using a L9 orthogonal array: phosphoric acid concentration, heating by microwave time, power from the microwave, and nitrogen flow rate. Findings indicated that the most important element for maximizing the production of AC from these agricultural leftovers was microwave power, along with the percentage of phosphoric acid and the time frame of the heating process.

This study examines the dynamics between the cultivation of biotech plants and food protection on a global scale from 2012 to 2018 which will ensure sustainability in food. The use of facts from the worldwide food security Index (GFSI) and biotech crop cultivation regions, we analyze modifications in food security metrics alongside developments in biotech crop adoption across various international locations. Our findings reveal intriguing patterns, including extensive increases in biotech crop cultivation in Brazil and the United States, coinciding with terrific enhancements in GFSI scores in nations like Chile, Uruguay, and Argentina. Conversely, a few countries, such as Burkina Faso and Myanmar, exhibited high-quality shifts in GFSI despite stagnant biotech crop cultivation. Furthermore, simultaneous will increase or decreases in each biotech crop cultivation and GFSI rankings were observed in positive international locations, underscoring the complicated interaction between biotech crop adoption and food security effects. Moreover, we discuss the importance of considering food security at each national and household stages, highlighting the need for nuanced analyses of biotech crop contributions to general food security.

Waste management has become an increasingly pressing issue due to urbanization, population growth, and economic development. According to World Bank projections, waste production will reach 3.4 billion tonnes by 2050. The paper is focused on detailed analysis of waste management techniques that has to be improved and resources to be maximized, to be able to deal with various types of waste, including agricultural waste, industrial waste, municipal solid waste (MSW), and electronic waste (e-waste). The advancement in the artificial intelligence in various fields has drawn the attention towards utilizing its benefits in achieving optimized management of different types of wastes also. The paper is focused on description of on-recyclable waste materials which can be transformed into energy by using waste-to-energy (WTE) technologies. The different types of wastes generated in different sectors are being studied with details on their quantity and challenges in handling the wastes. The literature highlights the performance analysis of various methodologies of waste handling in terms of their efficiency, economic impacts and ecological implications. The prediction models and their performance was discussed with respect to the R2 value and mean absolute error (MAE) root mean square error (RMSE) to find the most suitable algorithm. The conclusion suggested that these AI based optimization methods can bring about enhancement in the various waste to energy conversion process making the management of waste materials more sustainable and reliable.

By combining silicon-based microelectronics with micromachining technology, microelectromechanical systems (MEMS) have been identified as one of the most promising technologies for the 21st Century. With its microsystem-based devices and technologies, it will have a dramatic impact on the way we live and the way we live our lives. With an emphasis on both commercial applications and device fabrication methods, the paper provides an introduction to the field of MEMS. As well as discussing the range of MEMS sensors and actuators, the phenomena that MEMS devices can sense and act upon, and the major challenges facing the industry, the presentation discusses the challenges faced by the MEMS industry. An introduction to the field of MEMS is presented in this paper, which is divided into four sections. A section on MEMS introduces the reader to its definitions, history, current applications, and miniaturization-related issues. Photolithography, bulk micromachining, surface micromachining, and high-aspect-ratio micromachining are among the fundamental fabrication methods discussed in the second section, as well as assembly, system integration, and packaging of MEMS devices. A brief description of the basic principles of sensing and actuation mechanisms is provided in the third section, which discusses the range of MEMS sensors and actuators, as well as the phenomena that can be sensed or acted upon with MEMS devices. Toward the commercialization and success of MEMS, the final section illustrates the challenges facing the industry.

The escalating global demand for energy coupled with escalating environmental concerns has underscored the imperative of efficacious energy conversion from renewable reservoirs. Among these, wind energy has ascended as a pragmatic and ecologically conscientious solution. Its ascent, outpacing conventional fuels such as coal, underscores the necessity to comprehend its performance intricately. This study zeroes in on an airfoil model, subjecting it to a dual scrutiny encompassing empirical investigation and computational simulation. Employing Computational Fluid Dynamics (CFD) analyses executed in ANSYS software, the study prognosticates pressure and velocity patterns for the 2D iteration of the Model 1 airfoil by the National Advisory Committee for Aeronautics (NACA). This exhaustive scrutiny spans across velocities of 10 m/s and diverse angles of attack (-5°, 2°, and 8°). Remarkably, a robust 90% correlation manifests between the outcomes of empirical experimentation and computational simulation. Within the aerodynamic schema of the Horizontal Axis Wind Turbine (HAWT), the 8° angle of attack emerges as the vanguard, distinctly illustrating the pinnacle of optimal pressure distribution and velocity gradient. Noteworthy is the consistent augment in airfoil performance as the blade angle escalates, substantiated by elevated apex velocities and pressures in juxtaposition to the -5° and 2° angles. The findings of this inquiry engender a significant stride in airfoil refinement for the optimization of wind turbine blades, thereby conferring invaluable insights in the realms of blade design, aerodynamic contemplations, and the augmentation of wind turbine performance.

Through the use of smart sensors to monitor and regulate plant conditions, smart home gardening management systems can maximize resource utilisation and minimize human intervention. This study offers a new system that remotely controls the water supply to ensure optimal plant growth without the need for personal presence. The system uses the Blynk IoT platform to monitor soil moisture and water levels. A Raspberry Pi is used in conjunction with several sensors, such as a soil moisture sensor and a DHT11 sensor for temperature and humidity readings. The technology activates a motor to provide water to the plants automatically when the soil moisture level falls below a certain threshold. Users can remotely monitor and manage the system from their cell phones thanks to integration with the Blynk platform. The suggested method is an affordable and effective way to garden in your home, and it’s simply customizable to fit the requirements of different users.

This research presents a comprehensive investigation of progressed materials for high-efficiency sun-oriented cells, centring on perovskite, natural, and quantum-dot innovations. Through an efficient strategy enveloping fabric determination, amalgamation, characterization, device creation, and execution examination, the study accomplished an eminent proficiency of 22% in perovskite sun-based cells, beating natural (9%) and quantum dot-based cells (12%). Stability testing uncovered perovskite cells maintained 90% of their introductory productivity after 1000 hours, outperforming the comparative decay watched in natural (75%) and quantum dot-based cells (80%). Comparative investigations with related works underscored the centrality of our discoveries, counting experiences into exciton elements, feasible plan hones, and imaginative approaches to adaptable solar cell models.

This research examines the way to a carbon-neutral future by looking at the integration of renewable vitality sources and vitality capacity advances in feasible energy arrangements. Through a multidisciplinary approach, enveloping information collection, numerical modelling, and scenario investigations, the study investigates the flow of transitioning vitality frameworks. The optimization of energy capacity capacities is educated by scientific models, uncovering that as renewable infiltration increments (20%, 40%, and 60%), optimal capacity capacities rise correspondingly (300 MWh, 700 MWh, and 1200 MWh). Situation investigations illustrate that higher renewable entrance and appropriately measured energy capacity capacities lead to significant diminishments in CO2 outflows (25%, 45%, and 65%) while keeping up positive financial reasonability. Sensitivity investigations confirm the vigour of the models, showing the versatility to varieties in key parameters such as renewable asset accessibility, energy capacity productivity, and capital costs. A comparative investigation against related work underscores the competitiveness and uniqueness of the proposed approach, emphasizing the noteworthiness of numerical modelling in optimizing energy frameworks. This research contributes profitable insights for policymakers, industry partners, and analysts committed to exploring the complexities of accomplishing a carbon-neutral future. The discoveries displayed here, together with those from different studies crossing worldwide vitality exchange, green hydrogen production, and urban arranging, collectively contribute to the broader discourse on economic energy move.

This research investigates the transformative potential of nanotechnology in tending to water refinement challenges and advancing natural supportability. Carbon nanotubes and graphene were synthesized and joined into nanostructured channels, showing a well-defined arrangement with predominant basic keenness affirmed through SEM and XRD investigations. In comprehensive water decontamination tests, these channels showcased momentous efficiencies: overwhelming metals, such as lead (Pb) and cadmium (Cd), were expelled at rates outperforming 98% and 97%, individually; natural poison methylene blue displayed an amazing evacuation productivity surpassing 99.5%; microbial contaminant Escherichia coli was successfully killed, accomplishing a momentous expulsion effectiveness of 99.9%. Comparative investigations with related studies underscored the competitive or prevalent execution of the nanostructured channels. Additionally, a life cycle appraisal (LCA) highlighted the commitment to natural maintainability, uncovering generally moo nursery gas outflows (450 kg CO2e), vitality utilization (550 MJ), and asset consumption (10 kg) related to the filters’ whole life cycle. The inventive integration of nanotechnology into water treatment techniques exhibits the potential for effective, feasible, and intriguing approaches, laying the establishment for the advancement of progressed innovations fundamental for worldwide water resource conservation.

This study focuses on achieving effective deposition of a Ni and 15% ZrB2 particle mixture onto SS-304 substrate surfaces through meticulous preparation steps. Thorough cleaning of the SS-304 substrate using alcohol in an ultrasonic bath eliminated contaminants, ensuring optimal adhesion. Simultaneously, the Ni-ZrB2 mixture underwent preheating at 1200°C for 20 hours in a muffle furnace to eliminate moisture content, crucial for preventing coating defects. Uniform distribution of the preheated powder onto the substrate was crucial for consistent coating thickness. Microwave hybrid heating (MHH) using charcoal as a susceptor material overcame microwave reflection by rapidly heating the powder mixture. SEM analysis revealed a uniform dispersion of both Ni and ZrB2 particles across the substrate surface, indicating successful deposition and optimal adhesion. The cladding resulted in a significant improvement in surface hardness, with an increase of approximately 42.43%. The wear rate, measured at 0.00178 mm³/m, and the coefficient of friction, determined to be 0.246, provided crucial insights into the surface’s wear resistance and frictional behavior, confirming its suitability for applications requiring enhanced durability and performance. These findings highlight the efficacy of the microwave-assisted cladding process in enhancing SS-304 with Ni-ZrB2 composite coatings, paving the way for its utilization in various industrial applications.

This study investigates the enhancement of aluminum-based composite manufacturing through the utilization of ZrB2 reinforcement via Friction Stir Process (FSP). Achieving a uniform distribution of ZrB2 particles is crucial for optimizing material properties. The addition of ZrB2 nanoparticles using FSP has led to notable improvements in various mechanical properties of aluminum. Tensile strength increased by 20.25%, hardness by 35.67%, fatigue strength by 23.67%, and wear resistance by 29.45%. These enhancements underscore the effectiveness of nanoparticle reinforcement in fortifying aluminum matrices against mechanical stresses and wear mechanisms. The results demonstrate the potential of FSP-based techniques in tailoring the mechanical properties of aluminum-based composites for diverse applications. This research contributes valuable insights into advanced manufacturing methods for developing high-performance materials with enhanced mechanical characteristics, facilitating the advancement of aluminum composite technologies for industries requiring superior strength, durability, and wear resistance.

The science of ecology is incorporated into farm development and operation through agroecological techniques. A paradigm shift in agriculture is essential to combat hunger, adapt to climate trade, and mitigate environmental degradation. By doing this, researchers may further acknowledge the interdependence of farmed and nonfarmed landscapes and the variety of products and services that robust ecosystems offer, including resilience, nutrient cycling, and pest control, all of which can help sustain yields. Agro-ecology relies heavily on the knowledge and experience of farmers since it fosters independence and decreases reliance on costly outside resources. The concepts of sustainable intensification and agroecology are examined in this paper as additional strategies to address the global issue of increasing food production while lowering environmental impacts. Also, this study evaluates how effectively these approaches boost crop yields, lower environmental costs, and build resilience to climate unpredictability by closely examining existing programs, integrated management strategies, and field experiments. Supporting the findings is a comparative table that shows several techniques of sustainable intensification and how they have an effect on yields and environmental costs. In order to expand resilient, sustainable, and equitable food systems, a discussion of the necessity of a paradigm shift towards agroecological strategies is addressed in the paper's conclusion.

The world's population is expected to increase to 10 billion humans through the 12 months 2050, which poses an extreme venture to agriculture's potential to deliver the developing demand for meals in a sustainable way at the same time as minimizing unfavourable environmental outcomes. The rising need for food worldwide has led to the widespread usage of fertilisers. The widely used chemical fertilisers can improve crop production and expansion, but they are harmful to the environment, the soil, as well as the health of people. As a result, one of the most intriguing alternatives to conventional fertilisers is nanofertilizer. These synthetic materials consist of nanoparticles that are regulated in their delivery of macro-and micronutrients to the plant rhizosphere. The necessary nutrients as well as minerals are bound together either alone or in conjunction with nano-sized adsorbents in nano material-based fertilizers. Conventional fertilisation techniques have resulted in inefficiencies and environmental problems because they often rely on chemical fertilisers for phosphorus (P) and nitrogen (N). Consequently, nanotechnology-based fertilizers—also referred to as nano fertilisers, or NFs—have become a promising therapeutic option. Compared to conventional fertilisers, these NFs enhance crop yields, improve nitrogen uptake efficiency, and have a smaller negative impact on the environment. This paper explores at the evidence, applications, and benefits of NFs, focusing on how they could change farming practices and enhance the production of sustainably produced food.

Massive and unpredicted rainfall-induced landslides are becoming more common in India. 12.6% of the area of India is prone to landslides. This problem presents a comprehensive approach to addressing this critical need by leveraging the Internet of Things (IoT). The existing works mainly focus on vibration sensors and slope movement sensors which may lead to inadequate real-time data. Our proposed work uses rainfall measurement and soil moisture sensors with vibration and slope movement sensors, which increases the data precision and integration. The main ideology is to evacuate the landslide-prone area before the landslide occurs hence saving the lives of people. After detecting the landslide it sends warning alerts to the disaster management authorities in that particular area. As a result, the IoT-based landslide detection system presents a significant advancement in addressing the challenges posed by landslides by focusing on early detection and warning capabilities but also minimizes environmental impacts by facilitating proactive evacuation measures.

Building energy efficiency is now a top priority because of the major negative effects that may happen on the society, the economy, and the environment. In various parts of the world, several researchers have worked on ways of achieving methods that can use phasechange materials as thermal storage. This is because these technologies have the potential to greatly reduce energy consumption when combined with solar power. PCMs store thermal energy in ways quite different than ordinary construction materials. These materials make use of latent heat rather than sensible heat. Therefore, phase-changed materials possess a notable advantage over sensible heat thermal energy storage materials with respect to storing and releasing heat. As a result, this paper was concerned with exploring the possibility of building energy conversion and storage systems using phase change material.

As an essential initial step towards clean and sustainable energy, this research focuses on innovative materials and structural designs for maximizing solar energy conversion and harvesting. Modern solar thermal and photovoltaic system technologies and supplies are examined to show how alternative electricity has become less expensive and more sustainable. The primary focus is on complex ideas like multiple junctions and tandem solar cells, which increase the efficiency of single-junction systems. The review paper investigates innovative solar power storage solutions, involving battery technology and energy storage materials, to meet the increasing need for secure and easily available sources of clean energy. The research paper explores the technology and uses of flat plate collectors, tube collectors, and solar power plants and how those are used in residential and commercial solar thermal systems. Solar energy conversion efficiency and sustainability will improve with innovations in materials and architecture. Building-integrated photovoltaics (BIPV) is one of the easiest solar system architectures that can be integrated into any residential or commercial building. Quantum dot solar cells, photovoltaic (PV) solar energy frameworks, such as CIGS thin-film solar cells, and organic photovoltaics (OPVs). Organic photovoltaics are portable and lightweight but have a low energy conversion rate, whereas quantum dot solar cells have a high energy conversion rate but face fabrication challenges.

Eco-design is a crucial approach in achieving sustainable manufacturing, which seeks to reduce the environmental impact of products and processes throughout their lifecycle. This paper explores the principles and tools that are used in eco-design, providing an overview of the key concepts and methods for sustainable manufacturing. The principles of eco-design are centered on minimizing the environmental impact of products and processes through the use of renewable resources, reducing waste and emissions, and improving energy and material efficiency. The paper discusses these principles in detail and highlights the benefits that can be achieved by implementing eco-design in manufacturing. The tools and methods of eco-design include life cycle assessment (LCA), design for environment (DfE), and environmental management systems (EMS) whereas DfE involves designing products and processes to minimize their environmental impact. EMS provides a framework for managing environmental performance across an organization. The paper also discusses the challenges of implementing eco-design in manufacturing, including the need for collaboration across different functions within an organization, the availability of data and resources, and the complexity of the supply chain. Organizations can implement eco design by utilizing Life Cycle Assessment, eco-labeling, and Design for the Environment. This approach can help organizations initiate or improve sustainable production practices.

Biomaterials are essential to the development of neural interfaces, including brainmachine interfaces. Biomaterial methods improve neural interface functionality, compatibility, and longevity, enabling brain-device communication. An extensive investigation of biomaterials utilized in brain electrode arrays, neural probes, & implantable devices rely on how materials affect neural signals recording, stimulation, & tissue contact. It also investigates how biomaterials, bioelectronics and 3D printing could improve neural interfaces. Biomaterials modulate neuroinflammatory responses, enhance brain tissue regeneration, and promote neural interface longevity. This study shows the potential for change of biomaterial-based neural interfaces in neuroprosthetics, neurological rehabilitation, and fundamental neuroscience research, addressing the need for brain-machine relationship and neurotechnology innovation. These findings suggest expanding biomaterials research and development to advance and sustain neural interface technologies for future use.

"Personalized Job Opportunity Finder powered by Web Scraping" research presents a comprehensive exploration the development and implementation of an innovative Job Portal, aiming to redefine the traditional job search experience. The project leverages cutting-edge techniques and integration with prominent communication tools. The experimental setup involves meticulous web scraping from renowned job portals, Google and Apple, using Puppeteer and Cheerio for data extraction. The user interface is thoughtfully designed, featuring an intuitive registration form and a dynamic home page that showcases personalized job recommendations. The research delves into the advantages of scraping job data from top companies, showcasing its efficacy compared to traditional methods such as partnerships and direct job postings. Big companies such as Google, Apple and Meta don't use partnerships for most of its hiring, that makes it difficult for candidates who aspire careers at such companies. Direct partnerships may have delays in updating job listings, whereas scraping allows for more immediate access to new postings.

This research examines the optimization of the deployment of electric vehicle (EV) charging stations by using machine vision technology, which involves analyzing real-time data and geographical information. Geospatial data analysis reveals prospective sites for charging stations by considering population density and accessibility to roads, hence identifying regions with increased demand for electric vehicle charging. The assessment of electric vehicle (EV) traffic patterns highlights the ever-changing charging requirements at various times and places, underscoring the need of flexible deployment techniques. Furthermore, evaluating the costs of implementing the deployment and the capabilities of charging, it becomes apparent that there are compromises to be made between the initial expenditures of installation, the amount of power generated, and the quantity of charging stations. These trade-offs are essential for optimizing resources. The usage study of charging stations using machine vision reveals variations in the number of available charging points at different stations and the need for adaptive resource distribution timestamps, techniques. The examination of percentage change reveals notable fluctuations in population density, installation costs, and the availability of charging points. This information is crucial for making well-informed decisions about the deployment of charging infrastructure. Combining machine vision insights with geographical and traffic analyses presents a promising method to create data-driven strategies for the placement of EV charging stations. This approach addresses the changing needs of electric mobility and provides guidance to stakeholders for efficient and flexible charging solutions.

In order to increase system efficiency, lightweight materials are crucial in the automotive and aerospace sectors. In this work, iron oxide (Fe2O3) and cobalt (Co) were used as reinforcements, with aluminium alloy AA2014 serving as the matrix material. The metal matrix composites were made using the stir casting technique. The proportions of iron oxide and cobalt utilised as reinforcement in the composites were 2.5 wt % and 5 wt %, respectively. On the composite specimen created in accordance with ASTM E8, E9, and E23 standards, the mechanical properties of tensile, flexural, and impact strength were investigated. Investigations were also done on the hardness of the composites. The morphology of the composites was examined using an optical microscope.

The need for strong, lightweight materials has prompted the creation of innovative metal matrix composites based on aluminum. The properties of metal matrix composites that are uniformly dispersed with nanoparticles are much superior to those of monolithic alloy and microparticle-reinforced composites. The objective of this work was to create and evaluate a metal matrix composite reinforced with MoS2, SiC, and TiC that is a hybrid aluminum alloy, Al6061. It was also investigated how the weight percentages (3, 6, 9, and 12%) of MoS2, SiC, and TiC reinforcement affected the mechanical, morphological, tribological, and physical characteristics of the metal matrix composite. The addition of SiC and MoS2 increased the density of the reinforced Al6061 composite when compared to as-cast non-reinforced Al6061. It was found that the hybrid composite Al6061/12% SiC/4% MoS2 had the maximum density. The hybrid metal matrix composite's toughness increased as the proportion of TiC weight increased. The composite made of Al6061, 12% TiC, and 4% MoS2 had the maximum hardness, measuring 114.03 HV. The composite Al6061/12% TiC/4% MoS2 has the most ultimate tensile strength. The tribology analysis revealed that when applied stress increased from 10 to 50 N, mass loss increased dramatically. Because of the solid MoS2 lubricant and the development of the TiC layer at the contact zone, Double- and triple-reinforced specimens had less wear loss than non-reinforced specimens, as shown by the wear performance of hybrid composites. The main wear mechanisms of the composites were delamination wear and wear debris.

The current work examines the AlMg1SiCu alloy material through the stir casting process, where the Molybdenum Disulphide (MoS2 ) using three different variations of weight percentage (3 MoS2%, 6% MoS2, 9% MoS2) and 10% uniform proportion silicon carbide (SiC). The distribution of reinforcements such as Hard particle Silicon Carbide (SiC) and Soft particleMolybdenum Disulphide in the matrix was studied by looking at the microstructure of the composites before Tensile and Hardness test using Backscattered Secondary Electron image (BSE). A Brinell hardness tester was employed to determine the hardness of samples made of AlMg1SiCu alloy and hybrid metal matrix composites. Tensile test carried out using a Universal test Machine for AlMg1SiCu alloy and HMMC Samples. With an increase in MoS2 particle percentage, hybrid composites' tensile strength improves. With a AlMg1SiCu hybrid composite containing 10% SiC and 9% MoS2, the maximum tensile strength has been achieved.

No abstract available.

Metamaterials are artificially structured composite materials that show unusual properties not usually available in natural materials. In general, metamaterial structures and properties are anisotropic. A waveguide filled with an anisotropic metamaterial shows unique properties not achievable in conventional waveguides, such as propagation of backward waves and modes below the cut-off frequencies of the conventional fundamental mode, zero group velocity etc. The waveguide filler material can be anisotropic with the tensorial permittivity and permeability components having positive or negative values, and combinations thereof, giving rise to a rich variety of phenomena. Further, modes in a cylindrical waveguide filled with a hyperbolic metamaterial are described by unusual Bessel modes of complex orders. In many situations, the wave propagating region is isotropic, and it is enclosed by anisotropic metamaterials with different thicknesses and contrarily the propagating region is might be anisotropic that is enclosed by isotropic in some other situations. Various metamaterial waveguide geometries like a pair of parallel plates, waveguides with rectangular or cylindrical cross-section filled with anisotropic metamaterials as well as hollow-core waveguides with metamaterial claddings or linings have been demonstrated experimentally. The anisotropy can be uniaxial or biaxial depending on the orientation of structure. Here we review the advances in the theory and applications of waveguides filled with subwavelength structured metamaterials with anisotropic or even hyperbolic properties across the electromagnetic spectrum. By examining the field behaviour in such waveguides, connection is made to the extraordinary transmission of light through arrays of subwavelength sized apertures in a metallic screen. Potential applications range from enhanced MRI imaging and electromagnetic shielding at radio frequencies to intriguing imaging applications and efficient coupling of the emitted radiation from small sources into waveguides at optical frequencies.

This research paper explores Karnataka's pivotal role in the global transition to green hydrogen as a sustainable energy solution. While historically reliant on conventional energy sources, Karnataka's abundant renewable resources, including solar and wind potential, position it as a frontrunner in the green hydrogen revolution. The paper identifies and addresses challenges across technical, economic, regulatory, and infrastructure domains, offering innovative solutions and policy recommendations. It underscores the establishment of regional hydrogen clusters tailored to sectors like transportation, grid stability, industry, fuelling networks, rural electrification, and sustainable agriculture. From transforming transportation in Mangalore to driving industrial advancements in Belagavi, Karnataka's regional clusters offer tailored solutions for unique energy needs. The integration of green hydrogen into agriculture and irrigation practices in Kolar exemplifies the state's commitment to eco-friendly farming and sustainable development. Karnataka's visionary approach to green hydrogen not only demonstrates its dedication to environmental sustainability but also positions it as a pioneering player in the green hydrogen landscape, driving innovation, economic growth, and a clean energy future.

A prevalent form of cancer that affects millions of individuals globally is skin cancer. The visual examination of skin lesions, however, is a challenging and time-consuming procedure that calls for the knowledge of dermatologists. The proposed effort intends to create an accurate, feasible and effective system for detecting skin lesions that can help dermatologists identify and treat a variety of skin conditions. To extract features from skin lesion photos, the method uses a pre-trained Convolutional Neural Network (CNN). These characteristics are then fed into a Recurrent Neural Network (RNN) for temporal modelling. The early diagnosis of numerous skin illnesses depends greatly on the detection of skin lesions. Deep learning models, particularly CNNs, have demonstrated impressive performance in the computer-aided diagnosis of skin lesions in recent years. This work uses the HAM 10000 dataset to suggest a hybrid CNN and RNN model for skin lesion detection.

In recent years, Chemical Vapor Deposition (CVD) has emerged as a pivotal technique for the synthesis of high-quality nanomaterials, owing to its ability to produce uniform and scalable thin films with controlled properties. This study presents a comprehensive characterization and modelling of nanomaterials synthesized via CVD, elucidating the intricate relationship between process parameters and the resultant material properties. Utilizing advanced characterization techniques, including Transmission Electron Microscopy (TEM), XPS, and Raman Spectroscopy, we have discerned the morphological, compositional, and structural attributes of the synthesized nanomaterials. The experimental data were subsequently employed to develop a predictive model, leveraging machine learning algorithms, to forecast the properties of nanomaterials based on CVD parameters. The model exhibited high accuracy and can serve as a robust tool for optimizing CVD processes in real-time. Our findings underscore the potential of CVD in tailoring nanomaterial properties for specific applications and provide a foundational framework for researchers and industries aiming to harness the full potential of nanomaterials synthesized via CVD. This work not only advances our understanding of CVD-synthesized nanomaterials but also paves the way for their application in next-generation electronic, photonic, and energy devices.

Cardiotocography (CTG) is a method of monitoring fetal heart rate and uterine contractions during pregnancy. CTG is a methodology used to measure the fetal well-being in a pregnant woman. The objective of the paper is to reduce the fetal mortality. Data is being evaluated by applying pre-processing techniques, followed by Convolutional Neural Network (CNN) and dimensionality reduction using Principal Component Analysis (PCA). The approach adopted in the proposed method for detecting the fetal heart rate is evaluated using two methods, namely, conventional CNN and conventional CNN integrated with PCA. Using CNN algorithm around 77% has been achieved and CNN integrated with .PCA gave around 95% accuracy.

Over the past two decades, the field of civil engineering has witnessed a remarkable transformation with the integration of robotic technology in civil and infrastructures inspection. Robotic drone arms have emerged as a pivotal tool, offering unparalleled access to hard-to-reach areas and enabling comprehensive assessments of civil structures. This article presents a comprehensive review of the advancements, challenges, and applications of robotic drone arms for civil structure inspection over the last two decades. This article discusses the key developments in types of robotic drone arms, real-world applications, success stories, current challenges and future directions for civil and infrastructure inspection.

In an increasingly interconnected world, the ability to overcome language barrier has become a crucial requirement. for effective communication. Language translator headphones have emerged as a promising technological solution to facilitate seamless multilingual conversations. This research paper aims to evaluate their accuracy, usability, and potential impact on communication dynamics. The paper begins by discussing the significance of language translation technology in various domains, such as tourism, business, and diplomacy. It highlights the limitations of traditional translation methods and emphasizes the need for innovative as well as sustainable solutions that can enhance communication efficiency and convenience with the help of raspberry pi as a microcontroller.

In an epoch marked by escalating apprehensions regarding the depletion of resources and the destruction of the environment, the notion of closed-loop supply chains (CLSCs) has garnered recognition as a viable and sustainable resolution. The present study examines the interdependent connection between environmental conservation and economic advancement by analysing the recycling and re-manufacturing procedures inside closed-loop supply chains. This paper utilises an extensive case study to investigate the crucial significance of closed-loop supply chains in the processes of recycling and re-manufacturing materials and components. Through a comprehensive examination of the complex relationship between environmental benefits and economic advantages, this study reveals the diverse and nuanced effects that arise from the implementation of closed-loop systems in contemporary supply chain management. The study utilises a mixed-methods methodology, incorporating both quantitative and qualitative studies. The study used quantitative data to measure the extent to which recycling and re-manufacturing processes contribute to the decrease of raw material usage, energy consumption, and greenhouse gas emissions. The study highlights the capacity of closed-loop supply chains to promote circular economy concepts, reduce waste output, and mitigate the environmental impact of companies. This study provides valuable insights that may be utilised by practitioners, politicians, and corporations to make well-informed decisions that prioritise both environmental protection and economic growth in their supply chain strategy.

In a construction project of G+19 Hotel & Residence, there have been parking problem due to lack of sufficient land. So to minimize these problem double basement have been designed for parking floor. The basement excavation is not easy to excavate without proper protection work for retaining deep excavations. Soil at its natural form, in a construction site is not suitable to completely bear heavy surcharge loads. For such situations, the soil stability needs to be improved to enhance its strengthen capacity and decrease the expected landslide. There are some techniques for retaining deep excavations for basements which are used at site to take surcharge load during excavation. Depending upon the loading conditions and nature of soil at site, a Cast-In-Place Bored Piling by Rotary Bored Machine technique have been adopted. This paper gives the overview and concept of Cast-In-Place Bored Piling by Rotary Bored Machine, discusses their practical applications and problems faced to Quality Control.

Road quality degradation affecting on safety and comfort of road users. It is necessary to carry out regular assessments of the functional and structural condition of the pavement. Evaluation of functional and structural conditions is carried out to maintain the good quality of road services. This research aims to evaluate the functional and structural conditions using the Pavement Condition Index (PCI) method and the functional condition of the road using the International Roughness Index (IRI) method. The tool used in testing functional conditions is the Hawkeye 2000 car which generates Pavement Condition Index data for each road segment, then calculates the average PCI value and the conditions on the road segment. From the analysis of the functional condition of the road pavement, the Pavement Condition Index value was obtained for Kudus East Ring Road Section at 57.05 (Fair), Pati Ring Road Section at 60.57 (Fair), and Wangon-Menganti Road Section at 78.35 (Satisfactory). From the results of the analysis of the functional condition of the road pavement, the International Roughness Index value was obtained for Kudus East Ring Road Section at 5.16 (Medium), Pati Ring Road Section at 4.94 (Medium), and Wangon-Menganti Road Section at 4.64 (Medium). The results of the correlation of the 2 parameters using SPSS on each successive road section show "weak correlation" with r = 0.2754; "moderate correlation" with r = 0.5534; and "no correlation" with r = 0.0435.

Thiruvallur District in Tamil Nadu is one such district, with groundwater levels reaching depths of 50m to 60m below the surface. Growing populations, variations in land use patterns, reduction in rainfall depth, and other factors all contributed to an increase in water demand and a decrease in water potential. This affects the quality of groundwater as well. In this study, the variation of both Groundwater potential and Groundwater Quality is analyzed. The collected data has undergone thorough processing to ensure its accuracy and relevance for the area to be studied. (Thiruvallur District). The base map for the place to be analyzed and the well-map are created in the QGIS software with the data. The processed data is imported into the QGIS to create a database. With the database, the spatial variation between the stations is mapped. The temporal variation of the stations is carried out. The spatial map is done for the groundwater level and Groundwater quality parameters like pH, TDS, Cl, etc. The temporal variation is shown in the graph for the GW level and GW quality parameters with respect to the well-points.

There has been a lot of focus in recent years on finding ways to incorporate renewable energy systems, especially solar photovoltaic (PV) systems, into the existing electrical grid. Power conversion technologies that are both efficient and reliable are in high demand due to the expanding popularity of solar photovoltaic (PV) systems. Micro-inverters, which are module-based inverters placed on individual PV modules, have grown in popularity in recent years due to their decentralized design. However, the integration of solar micro-inverter into the electrical grid presents power quality challenges. This research article presents an experimental investigation and power quality analysis of a solar micro-inverter under various operating conditions such as dust and shade.

India is a country with a rapidly growing demand for energy. Currently, most of the country's energy demand is met by fossil fuels which are hindering our environment by contributing to greenhouse gas emissions and climate change. Green hydrogen produced from renewable energy sources is clean and free from the pollution which can reduce our country's dependency on fossil fuels. Building a green hydrogen community in India can help the country to transit into sustainable development and achieve net zero emissions. Our review shows that green hydrogen can be produced in India according to the geography of the different regions rich in renewable energy resources such as solar and wind power. Many states in India have high solar energy prospectus, high wind speeds and existing infrastructure and supply chain logistics that can be used for the production and distribution of green hydrogen. States such as Gujarat, Andhra Pradesh and Tamil Nadu have been identified by the Indian government as "renewable energy clusters" and aim to support the development of green hydrogen projects. Additionally, the Indian coastal area's seawater can be used as a water source for electrolysis. These coasts are windy and suitable for wind power generation and have access to excellent ports and transport infrastructure to transport green hydrogen. Overall, India has unlimited potential for green hydrogen production due to its abundant renewable energy sources and favourable geographical conditions. India can use this potential to become a major player in the green hydrogen market with the right political and regulatory framework.

In this work, leftover foundry sand and vermiculite were used as partial replacements for fine and coarse aggregates in hybrid fibre reinforced concrete (HFRC). The study also concentrated on HFRC mix percentage optimization to achieve desired attributes. By creating multiple HFRC mixtures with varied ratios of used foundry sand and vermiculite. The mechanical characteristics of the HFRC were assessed. Tests on the HFRC’s permeability, water absorption, and chloride ion penetration were used to evaluate its durability. In comparison to ordinary concrete, the study shows that adding foundry sand and vermiculite to HFRC increased its mechanical and durability attributes. It was discovered that HFRC has stronger compressive, splitting tensile, and flexural strengths than regular concrete. In comparison to conventional concrete, HFRC also showed less water absorption, permeability, and chloride ion penetration. The research also determined the HFRC mix ratio that produced the maximum flexural strength, splitting tensile strength, and compressive strength. Vermiculite made up 10% of the mix’s coarse aggregate replacement, while discarded foundry sand made up 20% of the mix’s fine aggregate replacement. Sustainable development now requires that waste materials be used in building. This study uses waste foundry sand (WFS) and vermiculite to assess the mechanical properties.

The utilisation of Multi-walled carbon nanotubes (MWCNTs) nanofluids is considered to be a highly efficient approach in the field of thermal engineering, specifically for the purpose of cooling electronic processors. The usage of a microchannel along with an electronic chip for liquid cooling of electronics presents a compelling substitute to the conventional bulky aluminium heat sinks. A minichannel heat sink employing MWCNTs nanofluid as a coolant is further enhanced in thermal and hydraulic performance. In order to analyze the performance of the minichannel heat sinks, a conjugate heat transfer model has been solved using the commercial software ANSYS-CFD. Theoretically, it showed that the presence of MWCNTs reduced thermal resistance and increased the thermal conductivity of liquid cooling system. The results reveal a maximum enhancement of in average heat transfer coefficient ( h ) for minichannel heat sink using MWCNTs as a coolant at volume 40%, 46%, and 52% concentrations of 0.25%, 0.5% and 0.75%. The performance evaluation shows that the overall performance of the minichannel heat sink using MWCNTs cooled minichannel heat sink at 0.75% volume concentration is roughly enhanced more as compared to water.

This paper presents the implementation and prototype of low cost, portable ventilator for patients who are in a no resource places and no primary care environment. This can be achieved by a squeezing the bag valve mask(BVM) inflating and deflating the bag with respect to the servo motor with the help of mechanism. The system contains an assist-control mode are also included in the prototype. Future versions of the device will have a pressure relief valve, PEEP capabilities, and a customizable inspiration to expiration duration ratio. The cost of this prototype is determined very much less than the mass manufacturing units of ventilators. The idea of cam based bag compression is a efficient way to achieve low cost, high efficiency in this work to aid in the crisis conditions to assist the needy people who have suffocation, and using IoT Technology , we can monitor the patient’s healthcare system through the specially made application to apply the required information about the patient’s health state, with the help of this technology, a doctor can monitor the patient’s health and giving treatments according to the information and based on the information, diagnosis will be given to the required patient.

Today's developing world makes environmental protection absolutely necessary. Numerous natural and man-made disasters were happening all around the planet. Forest fires are one such environmental catastrophe. Once it starts, the fire in the dense forest quickly engulfs the entire region, consuming everything in its path and igniting everything. On hot days, fire spreads more easily due to the dry conditions, decimating the grasses and trees in forested areas. To protect the ecosystems of the forest's flora and fauna, such forest fire calamities must be diminished. The objective of this endeavour is to create and put into use an Internet of Things (IoT)-based system that can anticipate and identify forest fires, alert the appropriate authorities to their specific location, and help firefighters put out the fire when it first starts. This would prevent the fire from engulfing a big area and allow for the implementation of preventative measures to put out any fires that might start in the near future.

Security is one of the important characteristics while transmitting the data particularly medical images and patient information over cyberspace without any loss of information. In the proposed method LWT, DCT and SHA-256 hashing techniques are used to provide security to the patient data and to detect tampers in ROI of the medical images. In this paper, medical image is segmented into three regions, region of interest (ROI), region of non interest (RONI) and BORDER regions. ROI is an area that has an important impact on diagnosis, whereas RONI has less or no significance in diagnosis. This paper proposed ROI based tamper detection that embeds hash value of ROI into RONI for authentication and also embed the patient information into RONI for providing security. The experimental results of the proposed method on various medical image databases proved to identify the tampers in medical images. Compared with the existing technique, the proposed method offered high Peak Signal to Noise Ratio (PSNR) approximately 59db for watermarked medical images.

The objective of this project is to design a driver unconsciousness detection system using image processing to detect drowsiness and unconsciousness in drivers, thereby preventing accidents resulting from driver fatigue. Driver fatigue is a serious road safety issue, with approximately 20% of all road accidents attributed to this cause. Conventional drowsiness detection systems rely on physiological monitoring, which can be unreliable, expensive, and challenging to implement and maintain. In contrast, the proposed system monitors a sequence of images to identify facial and behavioral patterns indicative of drowsiness or unconsciousness. By detecting facial landmark points and analyzing the duration of eye closure, the system can accurately classify the driver’s state and take appropriate measures such as reducing the vehicle’s speed and alerting emergency services of the driver’s geo-location. The successful implementation of this system holds immense potential for substantially reducing the number of accidents resulting from driver fatigue, thereby mitigating the loss of lives and injuries.