VOLUME 11, ISSUE 10, OCTOBER 2024

Abstract: Bangladesh has undergone exceptional urban expansion over the past fifty years, and this trend is expected to continue during the following fifty. However, the process of rapid urbanization has resulted in serious threats to the sustainability of communities, such as an increase in slums, a shortage of affordable habitations, insufficient amenities for local residents, various types of pollution, and so on. During the last 12 years, agricultural land has been declining on average at a rate of about 1%. The rapid loss of agricultural land in Bangladesh is primarily due to the expansion of rural housing facilities and the country's industrialized urban orientation. Providing housing for Bangladesh's growing population has been a major challenge for the country's arable land. If land is taken away for non-farm activities at the current annual rate, there won't be any cultivable land left in Bangladesh in 50 years. If the trend is not stopped soon, the country would permanently lose its food security, rendering its poor population more subject to volatile international commodity prices.

Keywords: Unplanned urbanization; Agriculture; Food security; Bangladesh.

Abstract: Building construction methods have evolved significantly over the years, reflecting advancements in materials, technology, and environmental awareness. Conventional methods, characterized by labor-intensive practices, have given way to modern techniques that emphasize efficiency, sustainability, and innovative design. This paper aims to contrast conventional and modern building construction methods by examining their materials, processes, cost implications, environmental impacts, and the role of technology. A critical comparison highlights the strengths and limitations of each approach, providing insights into their application in contemporary construction projects.

Keywords: Building construction, Construction industries, Environmental impact, Material cost

Abstract: Concrete is one of the most utilized construction materials globally, playing a crucial role in modern infrastructure development. Effective concrete mix design and quality assurance are paramount to ensuring the strength, durability, and performance of the structures. This review delves into the principles of concrete mix design, the importance of quality assurance protocols, and their implementation across diverse construction projects. By examining recent research and industry practices, the paper highlights key methodologies, challenges, and innovations in enhancing the reliability and sustainability of concrete in various construction environments. Concrete mix design and quality assurance are critical to the success of modern construction projects. By embracing innovative materials, digital technologies, and sustainable practices, the construction industry can build concrete structures that are not only strong and durable but also environmentally responsible. As the industry moves forward, continuous improvement in mix design and QA processes will be key to meeting the demands of an ever-changing world.

Abstract: Water scarcity and quality issues have long been prevalent in Rajasthan, particularly in its rural areas. Due to the region's arid climate, depleting groundwater levels, and increasing pollution of natural water sources, access to safe and clean drinking water remains a critical challenge. This review paper examines the urgent need for establishing water treatment plants in rural Rajasthan. It delves into the existing water challenges, the impact of poor water quality on health and development, and the benefits of implementing water treatment solutions. The paper also highlights potential strategies for setting up sustainable water treatment systems suited to the socio-economic conditions of rural communities in the state. Much of Rajasthan is arid or semi-arid, with a desert climate that naturally limits water availability. The region receives irregular and insufficient rainfall, making it difficult to replenish water sources. The excessive use of groundwater, mainly for agriculture and daily needs, has led to a significant decline in the water table, exacerbating the scarcity.

Abstract: Heritage structures, rich in cultural and historical significance, represent the pinnacle of ancient construction practices, craftsmanship, and material utilization. These structures have stood the test of time, embodying the architectural heritage of past civilizations. In contrast, modern construction practices emphasize efficiency, sustainability, and advanced technology. This paper undertakes a comparative study between heritage structures and modern construction practices by analyzing the materials, construction techniques, design philosophies, sustainability considerations, and challenges associated with each approach. Through this examination, the paper aims to shed light on how contemporary construction can learn from the past while embracing technological advancements for future developments.

Keywords: Heritage structures, Modern structures, Sustainability, Construction techniques, Monuments, Building technology

Abstract: Water scarcity is a significant challenge in rural areas, especially in semi-arid regions like Debari, Udaipur in Rajasthan, India. Effective rainwater recharge management can help address this issue. This review examines the use of Remote Sensing (RS), Geographic Information Systems (GIS), and field surveys to identify potential rainwater recharge points. These techniques provide comprehensive data for mapping, analysing, and implementing sustainable groundwater recharge strategies. The paper focuses on methodologies and case studies in the region, discussing the potential impacts on water conservation and agricultural sustainability. One of the most effective ways to address water scarcity in such regions is through rainwater harvesting and groundwater recharge. To identify potential recharge points, advanced technologies such as Remote Sensing (RS) and Geographic Information Systems (GIS) can be used in conjunction with traditional field surveys. These technologies provide valuable insights into the physical characteristics of the terrain, soil, land use patterns, and drainage systems, helping to locate areas where rainwater can be harvested and stored for future use.

Keywords: Remote Sensing, GIS, Rainwater recharge, Surveying, Rural region.

Abstract: A innovative bidirectional wireless electric vehicle (EV) charging system is presented in this work, facilitating Vehicle-to-Grid (V2G) applications and effective energy transfer between EVs and the grid. By combining communication protocols, power electronics, and wireless power transmission, the system enables convenient charging and high efficiency (>90%). Bidirectional energy transmission, smart grid integration, wireless charging (inductive/capacitive coupling), and communication protocols (Wi-Fi, Bluetooth) are some of the salient features. The method encourages better EV uptake, lower infrastructure costs, and increased grid stability. Successful V2G functioning and excellent efficiency (>92%) are demonstrated by experimental validation. By transforming the EV charging experience, this creative approach promotes environmentally friendly mobility. The suggested system supports the shift to a low-carbon transportation sector by providing a dependable, effective, and practical charging solution for upcoming EV applications.

Keywords: Electric vehicles, Bidirectional charging, wireless power transfer, vehicle-to-grid.

Abstract: A innovative bidirectional wireless electric vehicle (EV) charging system is presented in this work, facilitating Vehicle-to-Grid (V2G) applications and effective energy transfer between EVs and the grid. By combining communication protocols, power electronics, and wireless power transmission, the system enables convenient charging and high efficiency (>90%). Bidirectional energy transmission, smart grid integration, wireless charging (inductive/capacitive coupling), and communication protocols (Wi-Fi, Bluetooth) are some of the salient features. The method encourages better EV uptake, lower infrastructure costs, and increased grid stability. Successful V2G functioning and excellent efficiency (>92%) are demonstrated by experimental validation. By transforming the EV charging experience, this creative approach promotes environmentally friendly mobility. The suggested system supports the shift to a low-carbon transportation sector by providing a dependable, effective, and practical charging solution for upcoming EV applications.

Keywords: Electric vehicles, Bidirectional charging, wireless power transfer, vehicle-to-grid

Abstract: Udaipur, a city renowned for its lakes, relies on both natural and artificial water sources to meet its water supply needs. The primary sources of raw water in Udaipur are its lakes, including Fatehsagar, Pichola, Jaisamand, and Badi Lake. Additionally, groundwater sources such as wells and borewells supplement the city's water supply. The water supply system in Udaipur is managed by the Public Health Engineering Department (PHED) and the Municipal Corporation, which ensure the treatment and distribution of water to urban and peri-urban areas. The water is collected, treated through filtration and chlorination processes, and then distributed via an extensive network of pipelines. However, challenges such as growing population demands, water pollution, and seasonal fluctuations in lake water levels affect the city's water management efforts. Sustainable practices, improved infrastructure, and efficient water management are critical for ensuring an uninterrupted and safe water supply to the city.

Keywords: Water resources, Water supply system, Udaipur, Water pollution, Water treatment

Abstract: India faces significant challenges in managing its water resources due to growing population pressures, climate change, and the over-extraction of groundwater. Effective water resource management is essential to address these challenges and ensure sustainable development. Remote Sensing (RS) and Geographic Information Systems (GIS) offer powerful tools for the assessment, monitoring, and management of water resources in India. This paper explores the applications of RS and GIS technologies in the various stages of water resource management, including hydrological modelling, drought assessment, watershed management, and groundwater exploration. The paper also highlights the potential of these technologies in addressing India's water-related issues and improving water governance.

Keywords: Remote Sensing, Geographic Information system, Water Resource Management, Water governance, Sustainability

Abstract: Today, it is need to include critical practices in working mechanism. The inclusion of sustainable practices in working mechanism is needed to remove resilient and failures from the system and to exploit SCM factors effectually under manufacturing premises. Accordingly, in present study, seven pro-active practices are discussed and presented for retaining sustainability in manufacturing from the insights of Implication and development. In present study, seven practical elements named as Lean, Green, Kaizen, Preventive Maintenance, Digitalization of supply chain, Talent Management, and Redundancy under the zone of manufacturing are presented for advancement and retaining sustainability in manufacturing. The advance practical elements are presented for implication, development of model and devising a framework. The presented practices are critical and are discussed in detail in present study to impart knowledge based learning. The study can benefit managers of manufacturing organizations in understanding critical practices and allied metrics. The study presented tabulation of metrics related with pro-active manufacturing practices to help applicators in the development of sustainable framework.

Keywords: Sustainability, Manufacturing, Advance practices, Knowledge based study, Managerial framework

Abstract: Varicose veins is amongst the typical type of vascular condition which can turn in such chronic health issues without proper treatment. Existing diagnostic techniques include manual examination and doppler ultrasound these methods are very efficient but need considerable resources. The paper introduces an automated method for identifying varicose veins by utilizing the YOLO (You Only Look Once) deep learning algorithm. With real-time object detection of YOLO, the system is trained on a prepared set of labeled images wherein it learns to detect varicose veins accurately in several formats of images and video streams. It further enables the loading of images so that patients can be continuously monitored in an economical and accessible manner for healthcare professionals. This development is supposed to allow earlier detection and prompt medical action so as to improve the patients' health results and reduce the incidence of serious complications with varicose veins.

Keywords: Varicose Veins (V2), YOLO (You Only Look Once), Deep Learning, Object Detection, Image Analysis, Medical Imaging, Health Monitoring, Disease Detection, AI in Healthcare, Vein Identification, Image Classification, Medical Intervention.

Abstract: Poultry is one of the economic activities connected with the agriculture and industrial sectors. It is playing a prominent role while improving the socio-economic conditions of both rural and urban populace and provides income and employment opportunities to millions of people in India. Systematic survey was conducted to record the poultry farming and its entrepreneurial activity during April to May, 2024 using pre-tested questionnaire and personal visit to 135 poultry shops which are located at different places in Mysore city. Total 16 parameters were chosen to assess the socio-economic conditions of entrepreneurs. Results revealed that 39.3% adults (36-50 years), 34.8% middle aged (26-35 years), 15.5% youths (16-25 years) and only 10.4% aged (51 years and above) people were involved in poultry entrepreneurial activity. Majority (32.5%) of the entrepreneurs were literates and 15.5% were illiterates and 42.2% entrepreneurs had more experience (11 years) in poultry business. In Mysore, 63.9% shops involved in both eggs and meat (chicken) business who are doing it on small scale level. Moreover, 67.4% entrepreneurs unaware about poultry breeds. Total 63.8% entrepreneurs provided employment opportunity to laborers. Further, 41.8% entrepreneurs provided appropriate shelter, 75.5% entrepreneurs provide food and 37% entrepreneurs provided good space to poultry birds during their marketing. Furthermore, 74% entrepreneurs used both de-feathering and meat cutting machines and 97.2% entrepreneurs dispose the poultry waste generated during meat cutting by taking the help of Mysore City Corporation. However, poultry entrepreneurs need training to learn about the breeds and they should be made aware about the financial and technical assistance by concerned governmental and non-governmental organizations to get more returns and improve their socio-economic status further in Mysore. This measure could help enhance the poultry products such as eggs and meat production that in turn meet the consumers demand accordingly.

Keywords: Poultry, entrepreneur, Mysore

Abstract: Of all the cultural industries operating in Mizoram, none compares to the music industry in potential for generating a sustainable source of employment. The digital revolution has impacted this creative industry so severely that it is now a hotbed of innovation. This paper, in the first part, addresses the debate of whether Mizoram truly has a "music industry". Secondly, the paper posits certain stakeholders of the music industry as entrepreneurs through a synthesis of three well-established theories of entrepreneurship laid out down by Peter Schumpeter, R.S. Burt, and James E. Austin, Howard Stevenson and Jane Wei-Skillern. The paper concludes with a submission that a paradigm of self-organisation in the form of project management techniques must be laid out so as to develop a set of norms and practices for the local music industry. This is necessary for enhancing the capabilities of the stakeholders so that the industry can eventually be self-sustaining.

Keywords: Music industry, entrepreneurship, service marketing, project management.

Abstract: With the increasing demand for intelligent mobile applications, the deployment of large language models (LLMs) on Android devices has emerged as a significant challenge. Android platforms, being resource-constrained, require innovative solutions to effectively manage the computational and memory requirements of LLMs. This paper provides a comprehensive review of techniques such as transformer optimization, federated learning, quantization-aware training, and privacy-preserving inference for efficient LLM deployment on mobile devices. We explore the latest advancements in model compression, neural network optimization, and secure aggregation methods that enable on-device AI while ensuring performance, privacy, and user experience. This review emphasizes the trade-offs between model size, accuracy, and energy efficiency, offering practical insights into the development of next-generation AI-driven applications for Android devices.

Keywords: On-device AI, Android, large language models, federated learning, quantization-aware training, model compression, privacy-preserving inference.

Abstract: The purpose of the study was to find out the differences of mental health and stress between physical and non physical education students. Total 300 physical education and 300 other students selected for the study and their age ranged between 18-30years. The data was collected through respondents in the form of different tests. This study involves a cross sectional, comparative study of physical and non-physical education students. The research design of the study is to descriptive research design. The study depends mainly on primary source of data. The data was collected through respondents in physical and non-physical education students the Instructions was given to the sports person before filling the questionnaires. The data was collected through questionnaires. The instruction was given by the investigator to the students before filling these questionnaires. Non Physical Education students reported severe stress than physical education students. The findings of the study reveal that Physical Education Students was better Perceived general health as compared to Non Physical Education Students . The findings of the study reveals that Physical Education Students was sound Mental health as compared to Non Physical Education Students.

Abstract: Crowdfunding, indeed, has become the lifeline for entrepreneurs to fund their innovative ideas and projects. Despite its fantastic popularity, a traditional crowdfunding platform has been known to face plenty of challenges, including opacity, high transaction cost, and fraudulent activities. To this end, this paper reviews five innovative approaches that unlock blockchain technology for the reliability and efficiency of crowdfunding systems. Analysis of these methods would then lead to a framework of a more efficient crowdfunding model that will mitigate the existing problems while still leveraging the benefits of decentralized finance.

Keywords: Tokenised Crowdfunding, Peer -to- Peer Funding, Blockchain Crowdfunding Campaign, Transparency & Anti-Fraud, Immutable Records.

Abstract: This paper presents a strategy to foster computational thinking through an unplugged approach with university students at a tutoring fair. Forty-eight students from the bachelor's programs in Software Engineering, Education, Nursing, and Public Accounting participated. The activity, named Multidisciplinary Escape Room, was structured around the four pillars of computational thinking: decomposition, abstraction, pattern recognition, and algorithms. The dynamic also promoted skills such as problem-solving, collaborative work, time management, and logical reasoning in a playful environment. The multidisciplinary approach facilitated the application of computational thinking principles in contexts beyond computer science, demonstrating its transversality. The results indicate that these activities strengthen these competencies and promote skills across multiple disciplines, contributing to the comprehensive development of students..

Keywords: Higher Education, Escape Room, Gamification, Multidisciplinary, Computational Thinking.

Abstract: The increasing complexity of educational data demands advanced analytical methods beyond traditional evaluation metrics. This study investigates the application of Educational Data Mining (EDM) to analyze and predict students' academic performance effectively. It combines clustering methods, particularly an enhanced K-means algorithm, and deep learning techniques like Convolutional Neural Networks (CNN) to provide a comprehensive evaluation framework. The proposed approach focuses on improving the accuracy of performance prediction by determining optimal clustering numbers and using labeled data for deep learning. Results demonstrate significant improvements in identifying at-risk students and enhancing educational decision-making.

Keywords: Academic records, Attendance tracking, HTML (Hyper Text Markup Language) ,PHP CSS,JQuery, Bootstrap,Node.js,Course registration. component, formatting, style, styling,CNN,EDM

Abstract: Owning/keeping different species of pet animals has become a social norm in many countries. Pet animals are keeping as a symbiotic relationship by mankind as a source of companionship, pleasure and for protection that facilitates social interaction, fostering connections with other pet animal owners and members of the community. To record the pet animals keeping activity in Mysore, present investigation was conducted during March-June, 2024 by following standard methods. Altogether, 452 residents were selected randomly and grouped them into pet owners, non-pet owners, pet walkers and non-pet walkers at 32 areas which belong to newly established areas, old areas and outskirts of Mysore. More than ten parameters were considered to collect information on pet animals keeping activity using pre-tested questionnaire. Collected data was systematically complied and analysed using various standard methods, compared between different areas of Mysore using standard statistical tests. Results revealed quite interesting facts as follows. Distribution of pet owners, non-pet owners and pet owners walking with pets distributed at newly established areas in Mysore, old Mysore and outskirt area of Mysore belong to Karnataka and outside Karnataka indicated significant difference. Total 87 residents are new to pet animals keeping and 128 residents are practising pet animals keeping since second generation and only few (41) residents are practicing pet animals keeping since third generation of their family. In Mysore dogs, cats, fishes and birds are commonly used as pets and more number of pet animals are keeping in old Mysore area compared to new and outskirts of Mysore city. Further, majority of the pet owners keep pet animals for hobby and few residents keep pet animals for commercial purpose. Furthermore, highest number of pet owners (98) had 3 to 6 years of experience and 44 pet owners had 6 to 9 years of experience in keeping/rearing pet animals. Pet owners provide home-made food, dry kibbles, wet canned food, raw diet and mixed food to their pets with different feeding schedules which is not alike at different areas of Mysore. Veterinary care such as grooming and vaccination are provided to pet animals as per the standard norms. Every pet owner spend lakhs of rupees on their pet animals in Mysore. In conclusion, the study emphasizes the need for promoting responsible pet ownership and designing effective pet welfare programs to support the growing trend of pet ownership in urban areas like Mysore. These insights are vital for policymakers to maintain and manage pets, urban planners and the community to create pet-friendly environment that would contribute positivity among the owners and their pet animal's well-being.

Keywords: Pet animals, keeping activities, Mysore city

Abstract: Touchless heartbeat measurement using facial video represents a cutting-edge approach to non-invasive physiological monitoring, leveraging advancements in computer vision and machine learning. Traditional methods of heartbeat detection, such as contact-based sensors, can be uncomfortable or impractical for certain use cases. By contrast, this method uses facial video to capture subtle color changes and micro-movements in a person's face, which correlate with blood flow and heart activity. Through a series of algorithms, the video feed is processed to isolate these variations, calculate heartbeat signals, and deliver real-time measurements. This technology has a wide range of applications, including healthcare monitoring, mental health assessment, and fitness tracking, especially in scenarios where physical contact is undesirable or unfeasible. Additionally, the method provides a solution for remote, continuous monitoring, offering potential applications in telemedicine and home healthcare. Experimental results demonstrate that touchless measurement via facial video achieves reliable accuracy under controlled lighting and minimal movement, though challenges remain in adapting the technology to diverse environments and populations. The advancement of robust and adaptive algorithms is essential to overcoming these limitations and fully realizing the potential of contactless health monitoring.

Abstract: Educational content creation is evolving, with Generative AI leading a transformative approach to learning resources. Traditional methods of producing educational audio and visual materials often involve high costs, extended production times, and limited customization options. This paper, therefore, presents a unique solution that integrates GEN AI to automate high-quality audio and image generation for educational podcasts. By utilizing advanced AI techniques, this approach not only streamlines production but also enhances accessibility and engagement. An in-depth analysis of the system architecture and model selection offers a framework for creating educational podcasts that are both efficient and impactful, addressing the challenges of conventional content delivery.

Keywords: Generative Artificial Intelligence (GenAI), Natural Language Processing (NLP), Machine Learning (ML), Text-to-Speech Synthesis (TTS), Visual Generation, Podcasting, Education Technology, Audio-Visual Production

Abstract: This study explores the impact of AI-driven technologies in recruitment, particularly in fostering Diversity and Inclusion (D&I). As organizations adopt AI to streamline hiring, concerns arise over the potential for AI systems to unintentionally introduce biases, often due to reliance on biased training datasets or inadequate oversight. Through survey data analysis of HR professionals across various industries, this research examines the dual role of AI in enhancing recruitment efficiency and reducing human bias, while also facing limitations in subjective assessments like emotional intelligence and cultural fit. Findings indicate that AI is effective for technical skill evaluation and initial screening but remains challenged in areas requiring nuanced human judgment. Recommendations focus on regular AI audits, collaborative human-AI decision-making, improved transparency, and fostering an inclusive workplace culture. This paper provides insights into AI's evolving role in talent acquisition, highlighting the need for balanced, ethical practices that align with organizational D&I goals.

Keywords: AI in recruitment, diversity and inclusion, bias in AI, ethical hiring, fairness in algorithms, recruitment automation, AI transparency, inclusive hiring, candidate evaluation, organizational culture, data-driven hiring

Abstract: This research, entitled "Enhancing Teaching Performance through Technological Pedagogical Content Knowledge (TPACK): A Study of Mathematics Teachers in Private Institutions," examines the TPACK and teaching performance of 100 secondary mathematics educators in private institutions in Nueva Ecija. Research indicates that educators exhibit a good level of TPACK, reflecting confidence and proficiency in utilizing technology to improve mathematics instruction. The teaching performance of these educators is positively assessed, with teachers demonstrating excellence in fundamental instructional techniques, including lesson preparation, classroom management, and instructional clarity. However, several domains, particularly in accommodating individual student differences, were recognized as requiring additional assistance and enhancement to promote inclusive learning. The study reveals a substantial positive link between TPACK and teaching performance, emphasizing the essential significance of technological integration in enhancing teaching effectiveness. The findings indicate that focused professional development designed to improve teachers' TPACK may further elevate instructional quality and student engagement in mathematics. Furthermore, providing educators with techniques to accommodate varied learner demands may enhance the whole educational experience, rendering mathematics instruction more flexible and efficient.

Keywords: Mathematics Teachers, Private Institutions, TPACK, Technological Integration, Teaching Performance

Abstract: Machine Learning Operations (MLOps) has become essential for managing the lifecycle of machine learning models, from development to deployment and monitoring in production environments. As organizations increasingly rely on machine learning for critical applications, security concerns within MLOps pipelines have become paramount. This paper presents a comprehensive framework for integrating security into MLOps workflows, addressing risks such as data breaches, adversarial attacks, and model theft. We explore key architecture patterns, identify security challenges in MLOps platforms, and propose techniques for securing build and deployment processes. By embedding security into each phase of the MLOps lifecycle, organizations can mitigate risks and safeguard their machine learning investments.

Keywords: MLOps Security, Machine Learning, Adversarial Attacks, Secure Model Deployment, Data Security, Model Integrity.

Abstract: Explainable AI (XAI) is a rapidly advancing area within artificial intelligence, dedicated to enhancing the transparency and interpretability of AI models. This field addresses a major obstacle to AI's broader acceptance in critical domains like healthcare, finance, and legal services, where traditional AI systems often operate as "black boxes" with complex and opaque decision processes. XAI seeks to make these models more understandable, providing insights that are accessible to users. This paper delves into the significance of interpretability in AI, emphasizing how explainability fosters trust, accountability, and compliance with regulatory standards. Various techniques, including feature attribution, model distillation, and local interpretable model-agnostic explanations (LIME), are reviewed as tools to render AI decisions clearer and more reliable. By enhancing transparency, XAI not only aids in validating and debugging models but also tackles ethical issues related to bias and fairness within AI systems. This paper illustrates how XAI can bridge the divide between machine learning predictions and actionable insights, paving the way for AI systems that are both trustworthy and accountable. Through an analysis of current XAI methods and relevant case studies, the paper underscores XAI's potential to drive more ethically responsible and user-friendly AI solutions.

Keywords: Explainable AI (XAI), Interpretability, Transparency, Model distillation, Feature attribution, Local interpretable model-agnostic explanations (LIME), Trust in AI, Accountability, Regulatory compliance, Ethical AI

+91-7667918914 iarjset@gmail.com 0 Items International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal ISSN Online 2393-8021 ISSN Print 2394-1588 Since 2014 Home About About IARJSET Aims and Scope Editorial Board Editorial Policies Publication Ethics Publication Policies Indexing and Abstracting Citation Index License Information Authors How can I publish my paper? Instructions to Authors Benefits to Authors Why Publish in IARJSET Call for Papers Check my Paper status Publication Fee Details Publication Fee Mode FAQs Author Testimonials Reviewers Topics Peer Review Current Issue & Archives Indexing FAQ’s Contact Select Page A Transformerless Photovoltaic Inverter With Dedicated MPPT For Grid Application Mohammed Hisham, Shamrin Muhammedkutty P, Farzana P Abstract The goal of lowering the size and expense of grid-connected solar systems has led to a recent surge in interest in transformerless grid-connected inverter advancements. However, achieving the maximum power from individual modules is a significant restriction in such systems. A modular transformerless grid-connected solar multilevel inverter that can accomplish each module's maximum power point (MPP) under various operating conditions is proposed in this study. There is flexibility to expand the number of inputs with fewer components thanks to the straightforward and modular architecture that is being given. For the suggested system, a single-phase synchronous reference frame PI (SRF-PI) controller has been developed and implemented, and the methodical process for doing so has been explained.

Keywords: Mppt, Transformerless Inverters, Photovoltaic, Grid Tied. Downloads: | DOI: 10.17148/IARJSET.2024.111027 How to Cite: [1] Mohammed Hisham, Shamrin Muhammedkutty P, Farzana P, "A Transformerless Photovoltaic Inverter With Dedicated MPPT For Grid Application," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.111027 Copy Citation Call for Papers Rapid Publication 24/7 April 2026 Submission: eMail paper now Notification: Immediate Publication: Immediately with eCertificates Frequency: Monthly Downloads Paper Format Copyright Form   Submit to iarjset@gmail.com or editor@iarjset.com   Submit My Paper Author CenterHow can I publish my paper? Publication Fee Why Publish in IARJSET Benefits to Authors Guidelines to Authors FAQs (Frequently Asked Questions) Author Testimonials IARJSET ManagementAims and Scope Call for Papers Editorial Board DOI and Crossref Publication Ethics Editorial Policies Publication Policies Subscription / Librarian Conference Special Issue Info ArchivesCurrent Issue & Archives Conference Special Issue Copyright © 2026 IARJSET This work is licensed under a Creative Commons Attribution 4.0 International License. Open chat

Abstract: Cervical spine fractures represent a critical issue in healthcare, especially among older adults, where identifying these injuries can be complicated by existing degenerative conditions. In light of this, a recent study proposes an innovative method that harnesses deep neural networks (DNNs), particularly the U-Net architecture, to streamline the detection of fractures in computed tomography (CT) images. The focus of this methodology is to accurately identify and localize the cervical vertebrae, which is essential for a reliable assessment of fractures. By utilizing the U-Net's strengths in semantic segmentation, the model can effectively outline the boundaries of cervical vertebrae, capturing detailed features and spatial relations within the images. Additionally, the framework enhances the U-Net's fracture detection capabilities by adding multi-class classification layers, allowing it to differentiate between fractured and intact areas in the segmented vertebrae. This advancement significantly improves the diagnostic accuracy of the approach. Trained on a wide-ranging dataset of cervical spine injuries, this methodology presents substantial clinical benefits, such as facilitating real-time fracture assessments that lead to quicker diagnoses and timely interventions, ultimately enhancing patient outcomes. By tapping into the potential of deep learning, this approach promises to boost both the efficiency and accuracy of cervical spine fracture detection, contributing positively to patient care and treatment results.

Keywords: Key-words: U-Net architecture, computed tomography (CT) images, cervical vertebrae, semantic segmentation.

Abstract: The design of a drone frame plays a pivotal role in its overall performance, durability, and efficiency. This paper explores various factors influencing drone frame design, focusing on structural integrity, aerodynamics, material selection, and weight distribution. Drone frames must strike a balance between strength and lightness to support flight dynamics while withstanding environmental stressors such as wind, vibrations, and crashes. Materials like carbon fibre, aluminium, and composite polymers are often utilized for their lightweight properties and resilience. Moreover, frame geometry significantly affects a drone's manoeuvrability, stability, and payload capacity.

Keywords: Strength, Lightness, Stability and Payload Capacity.

Abstract: The job sequencing problem is an important branch of operations research where the order of processing jobs affects system performance. Due to vagueness and uncertainty in crisp theory sequencing problems are taken in which processing times are taken as fuzzy numbers. In this paper processing times are taken as trapezoidal fuzzy numbers and a new ranking function is proposed for determination of the optimal sequence of jobs, aiming to minimize the total elapsed time. Numerical example is given for demonstrating the proposed ranking function.

Keywords: Sequencing problem, trapezoidal fuzzy numbers, ranking function, optimal sequence, total elapsed time.